1 00:00:03,040 --> 00:00:05,280 Speaker 1: Welcome to Stuff to Blow Your Mind, the production of 2 00:00:05,360 --> 00:00:14,720 Speaker 1: My Heart Radio. Hey, welcome to Stuff to Blow Your Mind. 3 00:00:14,880 --> 00:00:17,720 Speaker 1: My name is Robert lad and I'm Joe McCormick, and 4 00:00:17,760 --> 00:00:19,959 Speaker 1: we're back with part two of our series on the 5 00:00:20,000 --> 00:00:22,840 Speaker 1: Coolest Shov Effect. Now, as I explained last time, this 6 00:00:22,880 --> 00:00:25,480 Speaker 1: is one that originally was going to be one episode. 7 00:00:25,480 --> 00:00:28,240 Speaker 1: We ended up splitting it into so we're doing a 8 00:00:28,240 --> 00:00:30,600 Speaker 1: little time traveling right now. This is an out of 9 00:00:30,640 --> 00:00:34,040 Speaker 1: sequence introduction, but I guess from here we'll just jump 10 00:00:34,159 --> 00:00:37,000 Speaker 1: right back into the middle of our conversation from last time. 11 00:00:37,280 --> 00:00:39,800 Speaker 1: Let's do it well anyway, So I wanted to talk 12 00:00:39,840 --> 00:00:45,200 Speaker 1: about very interesting paper that analyzed the history and meaning 13 00:00:45,200 --> 00:00:47,640 Speaker 1: of the cool Shov effect and then also tried to 14 00:00:47,760 --> 00:00:53,440 Speaker 1: recreate the Mojukan experiment. So this paper was published in 15 00:00:53,680 --> 00:00:58,360 Speaker 1: the Cinema Journal by Stephen Prince and Wayne E. Hensley, 16 00:00:58,520 --> 00:01:02,319 Speaker 1: called the Coolest Show Effect Recreating the classic experiment Your nine. 17 00:01:03,920 --> 00:01:07,000 Speaker 1: I think both of the authors on this paper were 18 00:01:07,080 --> 00:01:11,160 Speaker 1: at the time professors at Virginia Tech. Stephen Prince is 19 00:01:11,240 --> 00:01:13,640 Speaker 1: a is a film scholar who I know has done 20 00:01:13,640 --> 00:01:16,720 Speaker 1: a lot of work on a Kirakua Sawa. And I'm 21 00:01:16,720 --> 00:01:18,480 Speaker 1: not going to cover the entire paper, but I just 22 00:01:18,520 --> 00:01:20,640 Speaker 1: want to note some parts of it that struck me 23 00:01:20,800 --> 00:01:24,080 Speaker 1: as as relevant and interesting. So they start off by 24 00:01:24,360 --> 00:01:28,920 Speaker 1: telling the story of the Kolashov effect experiment, the experiment 25 00:01:28,959 --> 00:01:31,360 Speaker 1: with that actor Mojuk and making the neutral face and 26 00:01:31,400 --> 00:01:34,280 Speaker 1: then either being intercut with with soup or with the 27 00:01:34,319 --> 00:01:37,000 Speaker 1: woman in the coffin, and and the audience is raving 28 00:01:37,080 --> 00:01:40,240 Speaker 1: about how how expressive and powerful the emotions and the 29 00:01:40,280 --> 00:01:43,559 Speaker 1: performance were. Now, one thing they do at the beginning 30 00:01:43,600 --> 00:01:46,120 Speaker 1: is they note some differences in the details of the 31 00:01:46,120 --> 00:01:49,520 Speaker 1: story that arise from different recountings of it, and so 32 00:01:49,600 --> 00:01:53,760 Speaker 1: they end up casting doubt on whether the accounts of 33 00:01:53,800 --> 00:01:57,560 Speaker 1: this experiment are first of all, historically accurate and second 34 00:01:57,640 --> 00:02:01,320 Speaker 1: analytically valid, and so the author right quote. The goal 35 00:02:01,360 --> 00:02:04,800 Speaker 1: here is to provide a clearer contextualization of Kolashov's work, 36 00:02:04,880 --> 00:02:08,959 Speaker 1: distinguishing between its incontrovertible importance for an understanding of how 37 00:02:08,960 --> 00:02:14,240 Speaker 1: cinema communicates and certain of its limitations, especially it's incautious 38 00:02:14,360 --> 00:02:18,799 Speaker 1: merging of theoretical claim and observational assertion. As we will see, 39 00:02:18,919 --> 00:02:22,679 Speaker 1: Kulashev may have been right, but perhaps for the wrong reasons. 40 00:02:23,240 --> 00:02:25,320 Speaker 1: So the top line of this paper is that they 41 00:02:25,360 --> 00:02:28,840 Speaker 1: try to recreate the masu Can experiment as it is 42 00:02:28,919 --> 00:02:31,800 Speaker 1: usually described, and they do not produce the same result. 43 00:02:32,639 --> 00:02:35,960 Speaker 1: But this doesn't necessarily mean that the broader implications of 44 00:02:35,960 --> 00:02:39,840 Speaker 1: the Kolashov effect are wrong theoretically, but it might mean 45 00:02:39,880 --> 00:02:43,840 Speaker 1: something about the specific claims about a neutral face. Um. 46 00:02:44,200 --> 00:02:47,160 Speaker 1: So they start off talking about Kolashov's belief in the 47 00:02:47,240 --> 00:02:50,760 Speaker 1: power of montage and his arguments that editing is far 48 00:02:50,840 --> 00:02:54,160 Speaker 1: more important the meaning generated by a film than the 49 00:02:54,200 --> 00:02:57,080 Speaker 1: contents of the shots. So they talk about the masu 50 00:02:57,080 --> 00:03:00,000 Speaker 1: Can experiment, and then the other things we mentioned, creative 51 00:03:00,040 --> 00:03:04,560 Speaker 1: geography and creative anatomy, and they described the general takeaway 52 00:03:04,600 --> 00:03:10,760 Speaker 1: from the Mashukan experiment as follows quote. Naturalistic emotive performances 53 00:03:10,800 --> 00:03:14,800 Speaker 1: by actors were not considered by Kulashev to be essential 54 00:03:14,840 --> 00:03:19,000 Speaker 1: to cinema. Because of the demands of montage. Actors were 55 00:03:19,040 --> 00:03:24,560 Speaker 1: to provide minimal, restrained, and fairly unambiguous gestural and facial expressions. 56 00:03:25,120 --> 00:03:28,240 Speaker 1: As kola Chev puts it, quote, the presence of montage 57 00:03:28,360 --> 00:03:33,079 Speaker 1: necessitated that the shots should be constructed simply, clearly, distinctly. 58 00:03:33,639 --> 00:03:36,760 Speaker 1: Otherwise the flickering of a rapid montage would not be 59 00:03:36,840 --> 00:03:40,440 Speaker 1: sufficient for a full scrutiny of its contents, And then 60 00:03:40,440 --> 00:03:44,080 Speaker 1: the authors go on reacting partly against the over emoting 61 00:03:44,120 --> 00:03:47,640 Speaker 1: found in some silent films. Kulashov noted that quote a 62 00:03:47,720 --> 00:03:53,040 Speaker 1: preoccupation with psychologism rooted in the actor's performance was quite 63 00:03:53,200 --> 00:03:56,120 Speaker 1: useless for the cinema. So in a in a lot 64 00:03:56,160 --> 00:03:58,200 Speaker 1: of ways, it sounds like Kulashov kind of wanted to 65 00:03:58,240 --> 00:04:01,520 Speaker 1: take the acting out of acting. He's like, there's too 66 00:04:01,600 --> 00:04:04,960 Speaker 1: much psychology and acting. What we need instead is just 67 00:04:05,000 --> 00:04:08,960 Speaker 1: sort of like shots of actors doing kind of like plain, 68 00:04:09,160 --> 00:04:12,920 Speaker 1: unambiguous moments that can then be selected by the editor 69 00:04:13,400 --> 00:04:17,440 Speaker 1: to insert in a sequence to make meaning of m Yeah, 70 00:04:17,600 --> 00:04:19,839 Speaker 1: that's I mean, it reminds me of so many other 71 00:04:20,000 --> 00:04:25,280 Speaker 1: discussions we've had about performance and direction. Uh, I'm always 72 00:04:25,360 --> 00:04:28,320 Speaker 1: reminded of that that final sequence from a Geary The 73 00:04:28,360 --> 00:04:32,120 Speaker 1: Wrath of God, where you have you have what ends 74 00:04:32,200 --> 00:04:36,080 Speaker 1: up being a rather balanced and and and interesting performance 75 00:04:36,120 --> 00:04:39,680 Speaker 1: by klaus Kinsky. But apparently it's because Vernon Herzag just 76 00:04:39,839 --> 00:04:42,719 Speaker 1: wore him out, made him do take after take until 77 00:04:42,800 --> 00:04:46,479 Speaker 1: he wasn't doing like a frenzied um uh, you know, 78 00:04:46,960 --> 00:04:51,760 Speaker 1: over almost you know, overacting overly intense performance. He's not raging, 79 00:04:51,839 --> 00:04:55,279 Speaker 1: he's just actually, you know, emoting it at the level 80 00:04:55,320 --> 00:04:58,200 Speaker 1: that the director wants. And then can therefore be uh 81 00:04:58,600 --> 00:05:01,640 Speaker 1: be used effectively in the it. Yeah, And though if 82 00:05:01,680 --> 00:05:03,799 Speaker 1: that story is true, it may have worked in this case. 83 00:05:03,839 --> 00:05:06,839 Speaker 1: So I want to say I do not necessarily endorse 84 00:05:06,920 --> 00:05:12,600 Speaker 1: directing by exhaustion. No. Now that was a special relationship obviously, 85 00:05:13,120 --> 00:05:15,000 Speaker 1: But you often see this brought up, and you know, 86 00:05:15,040 --> 00:05:17,359 Speaker 1: there's this idea of like, is this is it the 87 00:05:18,520 --> 00:05:20,880 Speaker 1: is is this about the actor and the acting performance? 88 00:05:21,320 --> 00:05:25,159 Speaker 1: Is it about uh editing? Is it about the director's vision? 89 00:05:25,560 --> 00:05:27,400 Speaker 1: And you do often see that sort of push and 90 00:05:27,440 --> 00:05:29,880 Speaker 1: pull be it you know Klauskinski in vern or Herzog 91 00:05:30,000 --> 00:05:32,920 Speaker 1: or Jimmy Stewart and Alfred Hitchcock. Uh, you know, the 92 00:05:32,920 --> 00:05:35,560 Speaker 1: the actor has a certain vision about how things want 93 00:05:35,640 --> 00:05:37,880 Speaker 1: need to be, and then the director had maybe has 94 00:05:37,880 --> 00:05:41,359 Speaker 1: another idea not only about like this particular character in 95 00:05:41,360 --> 00:05:44,640 Speaker 1: this particular performance, but how it fits into the the 96 00:05:44,760 --> 00:05:47,960 Speaker 1: overall film, how it fits into the final edit. And 97 00:05:48,040 --> 00:05:50,080 Speaker 1: so you could have you can imagine somebody going into 98 00:05:50,120 --> 00:05:52,880 Speaker 1: it with this this sort of very Kula Shaw idea 99 00:05:53,000 --> 00:05:55,400 Speaker 1: of just shoot, all we needed just neutral actors, We 100 00:05:55,440 --> 00:05:58,320 Speaker 1: don't really need any any of this emotion one way 101 00:05:58,400 --> 00:06:01,400 Speaker 1: or another. And I don't know, there's probably some examples 102 00:06:01,400 --> 00:06:04,920 Speaker 1: of filmmakers who tend to lean in that direction with 103 00:06:04,920 --> 00:06:08,240 Speaker 1: with very neutral performances. Yeah, you could almost look at 104 00:06:08,279 --> 00:06:11,159 Speaker 1: that approach as uh, something that might be more common 105 00:06:11,200 --> 00:06:14,640 Speaker 1: saying like music videos and stuff than in narrative films. 106 00:06:14,680 --> 00:06:18,080 Speaker 1: Being probably find at some narrative films as well, where 107 00:06:18,240 --> 00:06:22,320 Speaker 1: the filming part of the filmmaking process is just sort 108 00:06:22,320 --> 00:06:25,680 Speaker 1: of like creating a bunch of building blocks that can 109 00:06:25,839 --> 00:06:30,080 Speaker 1: later be used in various arrangements to do whatever the 110 00:06:30,200 --> 00:06:33,679 Speaker 1: director or editor later decides to do with them. Yeah, 111 00:06:33,880 --> 00:06:36,560 Speaker 1: it also reminds me how, you know, a lot of 112 00:06:36,600 --> 00:06:39,080 Speaker 1: the films we're watching weird, how cinema will sometimes feature 113 00:06:39,839 --> 00:06:43,440 Speaker 1: non actors or you know, very very green actors. But 114 00:06:43,760 --> 00:06:47,520 Speaker 1: the right sort of non actor can really excel in 115 00:06:47,560 --> 00:06:49,919 Speaker 1: a scene if utilized correctly, you know, like not the 116 00:06:49,960 --> 00:06:52,479 Speaker 1: kind of non actor where they're just really outrageous with 117 00:06:53,160 --> 00:06:55,520 Speaker 1: you know, but uh, but where they're just sort of 118 00:06:55,880 --> 00:06:58,560 Speaker 1: very they're very neutral, they're they're almost barely there at all, 119 00:06:59,040 --> 00:07:01,360 Speaker 1: and if enough the other stuff is in the right place, 120 00:07:01,400 --> 00:07:03,640 Speaker 1: it can really work. Now. I gotta say, though, as 121 00:07:03,680 --> 00:07:07,360 Speaker 1: this paper ends up describing kola Chev's theory of film 122 00:07:07,400 --> 00:07:11,200 Speaker 1: and montage, I think I can't agree with with what 123 00:07:11,240 --> 00:07:13,920 Speaker 1: it sounds like Kolashov's vision actually was, because cool Chev 124 00:07:13,960 --> 00:07:17,360 Speaker 1: apparently said things like the film shot is not a 125 00:07:17,440 --> 00:07:22,120 Speaker 1: still photograph, the shot is a sign a letter for montage. 126 00:07:23,160 --> 00:07:25,720 Speaker 1: So I think he's saying like a still photograph can 127 00:07:25,760 --> 00:07:28,280 Speaker 1: have meaning on its own, but a shot in a 128 00:07:28,360 --> 00:07:32,360 Speaker 1: movie is more like a letter in a sentence, something 129 00:07:32,400 --> 00:07:35,240 Speaker 1: which does not have meaning on its own, but is 130 00:07:35,280 --> 00:07:38,840 Speaker 1: combined in sequence to make meaning. Clearly, that has some 131 00:07:38,960 --> 00:07:42,200 Speaker 1: truth to it, because, as we've said, editing does constitute 132 00:07:42,240 --> 00:07:44,720 Speaker 1: a major part of the the sense making or meaning 133 00:07:44,760 --> 00:07:47,720 Speaker 1: making of a film. But I think that's also pretty overstated. 134 00:07:48,000 --> 00:07:50,040 Speaker 1: You know, a lot of meaning lies in the editing, 135 00:07:50,040 --> 00:07:53,040 Speaker 1: but the contents of the shots also stand alone to 136 00:07:53,200 --> 00:07:56,040 Speaker 1: a greater extent and and matter a lot more than 137 00:07:56,120 --> 00:08:00,360 Speaker 1: Kolashov was giving credit here. Um. Though, again, to be fair, 138 00:08:00,440 --> 00:08:02,320 Speaker 1: I think it's important for us not to forget that 139 00:08:02,360 --> 00:08:05,800 Speaker 1: in the nineteen teens and early nineteen twenties. You know, 140 00:08:06,400 --> 00:08:09,400 Speaker 1: film was still fairly young, Editing was still fairly new 141 00:08:09,400 --> 00:08:13,120 Speaker 1: in cinema, and its powers were still being discovered. Uh. 142 00:08:13,160 --> 00:08:15,400 Speaker 1: You know, it's like, like we talked about the very 143 00:08:15,440 --> 00:08:18,760 Speaker 1: earliest films from the eighteen nineties and such, we're usually 144 00:08:18,800 --> 00:08:21,520 Speaker 1: not edited at all. They just be one continuous shot. 145 00:08:22,040 --> 00:08:25,320 Speaker 1: And even after editing was introduced, films of the Silent 146 00:08:25,400 --> 00:08:28,520 Speaker 1: era typically did not have as many cuts as movies 147 00:08:28,560 --> 00:08:32,480 Speaker 1: were used to today. Furthermore, the authors of of this 148 00:08:32,559 --> 00:08:36,240 Speaker 1: ninety two paper argue that a theory comparing film to 149 00:08:36,400 --> 00:08:39,280 Speaker 1: language is actually not super useful because there's just a 150 00:08:39,320 --> 00:08:41,880 Speaker 1: lot of ways in which that doesn't work. Like film 151 00:08:41,960 --> 00:08:44,520 Speaker 1: does things language cannot do, So you don't have to 152 00:08:44,640 --> 00:08:48,400 Speaker 1: learn a language to appreciate the meanings of films. You 153 00:08:48,400 --> 00:08:50,960 Speaker 1: you learn some conventions, but you know, you can just 154 00:08:51,000 --> 00:08:53,040 Speaker 1: watch a movie and make some sense of it even 155 00:08:53,080 --> 00:08:56,320 Speaker 1: if you're not familiar with conventions. As you to understand 156 00:08:56,320 --> 00:08:59,560 Speaker 1: the language, you have to learn the language. Um. Meanwhile, 157 00:09:00,040 --> 00:09:03,360 Speaker 1: language does things that film can't do, like photographic images 158 00:09:03,559 --> 00:09:06,800 Speaker 1: used in a film cannot be recombined freely to make 159 00:09:06,920 --> 00:09:10,520 Speaker 1: endless meaning the way a language can. There's also an 160 00:09:10,559 --> 00:09:14,240 Speaker 1: interesting digression in this paper about Kolashaw being influenced by 161 00:09:14,280 --> 00:09:18,360 Speaker 1: the ideology of industrial efficiency on the model of the 162 00:09:18,400 --> 00:09:23,400 Speaker 1: American engineer Frederick Taylor, who was a big proponent of 163 00:09:23,440 --> 00:09:26,600 Speaker 1: finding ways to make you know, production processes and factories 164 00:09:26,679 --> 00:09:30,280 Speaker 1: more efficient, finding all the places where where waste and 165 00:09:30,280 --> 00:09:33,439 Speaker 1: and and problems creep in and eliminating those, And that 166 00:09:34,040 --> 00:09:38,360 Speaker 1: Taylor's ideas of industrial efficiency were apparently very popular in 167 00:09:38,400 --> 00:09:42,239 Speaker 1: the Soviet Union at the time, and that in a way, 168 00:09:42,679 --> 00:09:46,679 Speaker 1: the authors say that you could view Kolashav's emphasis on 169 00:09:46,800 --> 00:09:51,319 Speaker 1: economy and acting as a type of industrial efficiency technique 170 00:09:51,320 --> 00:09:54,480 Speaker 1: applied to film theory. Yeah, And based on what I 171 00:09:54,520 --> 00:09:56,440 Speaker 1: was reading it, it doesn't. It does seem like a 172 00:09:56,440 --> 00:09:58,440 Speaker 1: lot of his work was based in let's figure out 173 00:09:58,520 --> 00:10:02,000 Speaker 1: what's working, and then how we can we can do that? 174 00:10:02,200 --> 00:10:04,440 Speaker 1: How how do we make how do what is the 175 00:10:04,440 --> 00:10:08,920 Speaker 1: most economic means of making effective film? Now? Ultimately, Prince 176 00:10:08,960 --> 00:10:12,600 Speaker 1: and Hensley make the case that Koulishov really was trying 177 00:10:12,640 --> 00:10:16,960 Speaker 1: to dress up his theoretical convictions about how film works 178 00:10:17,760 --> 00:10:20,880 Speaker 1: with the imper mater of empirical science with this alleged 179 00:10:20,960 --> 00:10:24,360 Speaker 1: experiment them as you can experiment uh and I think 180 00:10:24,360 --> 00:10:26,880 Speaker 1: I'm pretty convinced by their description of it that way. 181 00:10:26,920 --> 00:10:28,599 Speaker 1: I think this is something you've always got to be 182 00:10:28,679 --> 00:10:32,120 Speaker 1: cautious of because obviously, you know, I don't object in 183 00:10:32,200 --> 00:10:37,960 Speaker 1: principle to exploring or building upon artistic theories with empirical methods, 184 00:10:38,440 --> 00:10:40,640 Speaker 1: But I would also say, my personal opinion is that 185 00:10:40,720 --> 00:10:44,920 Speaker 1: a lot of these efforts to inject scientific methods into 186 00:10:45,240 --> 00:10:50,559 Speaker 1: esthetics and and art and stuff can be confusing and unnecessary. Like, 187 00:10:50,920 --> 00:10:54,160 Speaker 1: I don't think you have to have an empirical scientific 188 00:10:54,280 --> 00:10:57,920 Speaker 1: justification for an opinion about where meaning comes from in 189 00:10:58,120 --> 00:11:00,480 Speaker 1: art or in film. Obviously, I'm a huge believer in 190 00:11:00,600 --> 00:11:04,040 Speaker 1: empirical science. I just don't think it has to pervade 191 00:11:04,120 --> 00:11:08,839 Speaker 1: every domain, Like aesthetics and art don't necessarily need scientific 192 00:11:08,880 --> 00:11:11,920 Speaker 1: evidence and theories behind them. That those fields just you know, 193 00:11:12,280 --> 00:11:14,920 Speaker 1: work by different standards. And I think also a lot 194 00:11:14,920 --> 00:11:20,600 Speaker 1: of times if you try to generate empirical scientific justifications 195 00:11:20,679 --> 00:11:24,760 Speaker 1: for your beliefs about art or aesthetics or whatever, you're 196 00:11:24,800 --> 00:11:27,600 Speaker 1: often just gonna end up doing sloppy experiments or drawing 197 00:11:27,720 --> 00:11:32,239 Speaker 1: unjustified conclusions, even if you do a good one. Yeah, um, 198 00:11:32,280 --> 00:11:34,560 Speaker 1: Like I'm reminded, you know, of the fact that obviously 199 00:11:34,600 --> 00:11:36,520 Speaker 1: you have a such thing. There's such a thing as 200 00:11:36,679 --> 00:11:41,840 Speaker 1: outsider art and outsider cinema. Um and and examples of 201 00:11:41,880 --> 00:11:45,120 Speaker 1: outsider art and outsider cinema can be amazing, uh, you know. 202 00:11:45,400 --> 00:11:48,400 Speaker 1: And on the other side of things, you don't hear 203 00:11:48,440 --> 00:11:54,959 Speaker 1: as much about maybe outsider architecture, outsider structural engineering, things 204 00:11:54,960 --> 00:11:58,959 Speaker 1: of this nature. Outsider medicine is probably you know, best 205 00:11:59,200 --> 00:12:02,040 Speaker 1: avoided if you can, no matter how it's being dressed up. Well, 206 00:12:02,120 --> 00:12:05,200 Speaker 1: I mean, I think empirical methods are good for fields 207 00:12:05,200 --> 00:12:09,720 Speaker 1: in which you are trying to achieve very clearly specified goals, 208 00:12:09,880 --> 00:12:13,640 Speaker 1: certain kinds of outcomes and get them as reliably as possible. 209 00:12:14,040 --> 00:12:18,000 Speaker 1: And empirical methods are are less important in fields where 210 00:12:18,080 --> 00:12:21,319 Speaker 1: you're you're just trying to be expressive or be creative 211 00:12:21,360 --> 00:12:24,880 Speaker 1: and see what kind of emergent results come out. But 212 00:12:24,920 --> 00:12:27,840 Speaker 1: if it's like like this turns my mind to like 213 00:12:27,880 --> 00:12:33,199 Speaker 1: a B. Testing and focus groups used in film and television, um, 214 00:12:33,240 --> 00:12:35,560 Speaker 1: you know, not not necessarily a bad idea at all, 215 00:12:35,640 --> 00:12:38,120 Speaker 1: especially when you're dealing again with a very mainstream product 216 00:12:38,200 --> 00:12:40,800 Speaker 1: you want to appeal to a you know, a wide 217 00:12:40,800 --> 00:12:44,400 Speaker 1: population of individuals. Um. But you know, there are plenty 218 00:12:44,400 --> 00:12:46,320 Speaker 1: of arguments to be made about it as a potential, 219 00:12:46,600 --> 00:12:49,520 Speaker 1: you know, sloppy experiment. As you say, perhaps one of 220 00:12:49,520 --> 00:12:52,360 Speaker 1: the best critiques of all of this is that that 221 00:12:52,400 --> 00:12:55,000 Speaker 1: episode of The Simpsons, the Itchy and Scratchy and Pucci Show, 222 00:12:56,840 --> 00:13:00,360 Speaker 1: one of my favorites. It's just an old, creaky mirror. 223 00:13:00,480 --> 00:13:04,440 Speaker 1: Sometimes it sounds like it's coughing or talking softly. Yes, 224 00:13:12,280 --> 00:13:15,280 Speaker 1: But anyway to come back to uh, Prince and Henley's 225 00:13:15,320 --> 00:13:22,079 Speaker 1: description of methodological problems with the common descriptions of Kolashov's 226 00:13:22,120 --> 00:13:25,040 Speaker 1: alleged experiment the Masukan experiment with the neutral face and 227 00:13:25,080 --> 00:13:27,280 Speaker 1: the soup and the and the coffin and stuff. And 228 00:13:27,280 --> 00:13:29,720 Speaker 1: they list a bunch of questions, they say, quote for 229 00:13:29,800 --> 00:13:33,160 Speaker 1: such a seminal and basically uncontested study. There is virtually 230 00:13:33,200 --> 00:13:37,720 Speaker 1: no information available about Kolashov's actual method and procedure. Did he, 231 00:13:37,840 --> 00:13:41,160 Speaker 1: for example, interview the subjects individually or in a group? 232 00:13:41,520 --> 00:13:43,840 Speaker 1: What did he tell them beforehand about the purpose of 233 00:13:43,880 --> 00:13:46,760 Speaker 1: the presentation, What if anything, did he tell them about 234 00:13:46,760 --> 00:13:49,880 Speaker 1: the nature of film editing or montage. What was the 235 00:13:49,920 --> 00:13:52,840 Speaker 1: frequency of outlier opinions e g. People who did not 236 00:13:53,120 --> 00:13:57,679 Speaker 1: think Masouken was saddened by the dead woman. Published accounts 237 00:13:57,720 --> 00:14:02,160 Speaker 1: suggest the responses were uniform as this. So, unfortunately we 238 00:14:02,200 --> 00:14:05,120 Speaker 1: do not know the answers to any of these questions. 239 00:14:05,160 --> 00:14:10,120 Speaker 1: So given these limitations, they attempt to recreate and try 240 00:14:10,160 --> 00:14:12,680 Speaker 1: to replicate as best they can the conditions of the 241 00:14:12,679 --> 00:14:15,520 Speaker 1: original experiment to see if they get the same result. 242 00:14:16,200 --> 00:14:18,760 Speaker 1: So what they did was they put together a videotape 243 00:14:18,920 --> 00:14:22,720 Speaker 1: that they had some auditions for actors to produce a 244 00:14:22,720 --> 00:14:25,480 Speaker 1: close up shot of a face that was just totally 245 00:14:25,520 --> 00:14:27,400 Speaker 1: neutral and expression list. And they had to go through 246 00:14:27,440 --> 00:14:30,320 Speaker 1: a couple of rounds because in the first round the 247 00:14:30,360 --> 00:14:33,760 Speaker 1: actor's neutral face was not perceived as neutral enough by 248 00:14:33,800 --> 00:14:37,640 Speaker 1: the control group. Um. But so so they got a 249 00:14:37,640 --> 00:14:40,280 Speaker 1: neutral face on a video and they did the same thing. 250 00:14:40,320 --> 00:14:43,320 Speaker 1: They intercut it with a woman lying in a coffin, 251 00:14:43,960 --> 00:14:46,040 Speaker 1: a girl playing with a Teddy bear, and a bowl 252 00:14:46,040 --> 00:14:48,600 Speaker 1: of soup on a table, and they tried as best 253 00:14:48,600 --> 00:14:52,680 Speaker 1: they could to follow Kolashov's cues about what what the 254 00:14:52,680 --> 00:14:55,560 Speaker 1: cinematography techniques for making this work the best would be, 255 00:14:55,880 --> 00:14:58,840 Speaker 1: so it would be uh people visible on a darkened 256 00:14:58,920 --> 00:15:02,760 Speaker 1: black velvet back ground. Apparently the actors were told that 257 00:15:02,800 --> 00:15:06,080 Speaker 1: they just needed someone to uh to model for an 258 00:15:06,120 --> 00:15:09,360 Speaker 1: instructional video in which they would be required to do 259 00:15:09,400 --> 00:15:13,040 Speaker 1: an expressionless or neutral face. So one difference is that 260 00:15:13,120 --> 00:15:15,960 Speaker 1: instead of one long sequence intercutting with all of them, 261 00:15:16,000 --> 00:15:20,200 Speaker 1: they did separate sequences for each reaction. So, for example, 262 00:15:20,200 --> 00:15:24,720 Speaker 1: it might go face soup, face fade out or face coffin, 263 00:15:24,840 --> 00:15:28,000 Speaker 1: face fade out, and each shot was seven seconds long. 264 00:15:28,600 --> 00:15:30,920 Speaker 1: And the separate sequences make sense to me because you 265 00:15:31,000 --> 00:15:33,960 Speaker 1: might get a different reaction with some pairings than you 266 00:15:33,960 --> 00:15:37,640 Speaker 1: would with others. So viewers each saw one sequence selected 267 00:15:37,680 --> 00:15:40,080 Speaker 1: at random, and they were told that the experimenters needed 268 00:15:40,120 --> 00:15:44,040 Speaker 1: help evaluating an acting performance, and then the viewers were 269 00:15:44,080 --> 00:15:46,640 Speaker 1: supposed to select from a list of emotions that they 270 00:15:46,680 --> 00:15:55,280 Speaker 1: thought were being portrayed by the actor. Options included happiness, sadness, anger, fear, surprise, disgusted, hunger, 271 00:15:55,640 --> 00:16:00,240 Speaker 1: no emotion, and other Apparently the participants were underground adds 272 00:16:00,240 --> 00:16:03,040 Speaker 1: at a mid Atlantic university I'm going to assume based 273 00:16:03,040 --> 00:16:07,760 Speaker 1: on the author's affiliations, this was probably Virginia Tech. They 274 00:16:07,760 --> 00:16:11,920 Speaker 1: said that interestingly, film students were excluded from the experiment 275 00:16:11,960 --> 00:16:15,880 Speaker 1: since they might detect the connection to Kolashov and understand 276 00:16:15,920 --> 00:16:18,760 Speaker 1: what the experiment was getting at, which could bias results. 277 00:16:19,240 --> 00:16:21,840 Speaker 1: And in support of this decision, I mean, it seems 278 00:16:21,840 --> 00:16:24,400 Speaker 1: like a good choice either way. But to justify this decision, 279 00:16:24,760 --> 00:16:28,520 Speaker 1: they wrote about another recent attempt to replicate the Moso 280 00:16:28,600 --> 00:16:33,360 Speaker 1: Can experiment in France among film students who allegedly gave 281 00:16:33,400 --> 00:16:36,680 Speaker 1: answers like the following quote. We know that the man 282 00:16:36,720 --> 00:16:39,600 Speaker 1: does not change his expression, but because of the montage, 283 00:16:39,680 --> 00:16:43,000 Speaker 1: we think we see him change or quote. We know 284 00:16:43,120 --> 00:16:47,080 Speaker 1: the Kolashov effect and it works. And then Prince and 285 00:16:47,160 --> 00:16:49,440 Speaker 1: Hensley also had a control condition where they showed the 286 00:16:49,480 --> 00:16:52,440 Speaker 1: face to UH twenty four film students this time but 287 00:16:52,520 --> 00:16:55,880 Speaker 1: without any inner cutting. They were just showing them the 288 00:16:55,920 --> 00:16:58,720 Speaker 1: face by itself and asking them what emotion it was 289 00:16:58,720 --> 00:17:02,359 Speaker 1: showing for the face that they actually used in the experiment. 290 00:17:03,040 --> 00:17:05,280 Speaker 1: Percent said there was no emotion on the face, So 291 00:17:05,359 --> 00:17:08,200 Speaker 1: this is a very good neutral face. You know that. 292 00:17:08,200 --> 00:17:11,240 Speaker 1: That reminds me though of of use of neutral face 293 00:17:11,560 --> 00:17:15,440 Speaker 1: uh sort of not still pictures but just seen sequences 294 00:17:15,480 --> 00:17:18,280 Speaker 1: where um, a character and an individual is staring directly 295 00:17:18,280 --> 00:17:22,280 Speaker 1: into the camera. UM. I'm thinking it is certainly about 296 00:17:23,520 --> 00:17:27,560 Speaker 1: Ron Fricks film Baraka, which features a number of these 297 00:17:27,920 --> 00:17:30,919 Speaker 1: UH sequences where you'll you'll just have an individual from 298 00:17:30,960 --> 00:17:33,560 Speaker 1: from one culture or another just staring into the camera. 299 00:17:34,160 --> 00:17:37,280 Speaker 1: Or another example that comes to mind is the film 300 00:17:37,320 --> 00:17:39,560 Speaker 1: The Mission, where at the very end of the film 301 00:17:39,600 --> 00:17:43,000 Speaker 1: there's you just have several beats of one of the 302 00:17:43,040 --> 00:17:48,240 Speaker 1: primary characters, UH staring into the camera and very neutral expression. 303 00:17:48,640 --> 00:17:51,800 Speaker 1: And of course you have the entire film you've just 304 00:17:51,840 --> 00:17:56,240 Speaker 1: watched to help UH inform your idea of what's going 305 00:17:56,280 --> 00:18:00,000 Speaker 1: through that that character's head. Um. But but but still 306 00:18:00,119 --> 00:18:02,240 Speaker 1: it's it's a it's a great use of neutral expression, 307 00:18:02,320 --> 00:18:05,080 Speaker 1: like he doesn't it doesn't look particularly sad in that case, 308 00:18:05,960 --> 00:18:09,320 Speaker 1: but you in you can see sadness in the character. 309 00:18:09,440 --> 00:18:11,840 Speaker 1: You know, Well, yeah, that's a good example. But I 310 00:18:11,880 --> 00:18:14,880 Speaker 1: think it also does raise questions about something that's supposed 311 00:18:14,920 --> 00:18:19,760 Speaker 1: to be sort of outside the standard interpretation of this 312 00:18:20,200 --> 00:18:22,359 Speaker 1: of this experiment, which is like, well, wait, what are 313 00:18:22,359 --> 00:18:25,160 Speaker 1: the actual contents of the face? Maybe that does matter 314 00:18:25,760 --> 00:18:27,920 Speaker 1: that's going to come up in the author's interpretation of 315 00:18:28,000 --> 00:18:30,800 Speaker 1: the results they get. But so in the actual experiment 316 00:18:30,840 --> 00:18:33,280 Speaker 1: they did, they had a hundred and thirty seven participants, 317 00:18:33,320 --> 00:18:37,440 Speaker 1: including the control group in the experimental group in every condition, 318 00:18:37,840 --> 00:18:40,919 Speaker 1: whether it was soup, coffin, or child, the majority of 319 00:18:41,359 --> 00:18:44,159 Speaker 1: people said there was no emotion. So they saw the 320 00:18:44,160 --> 00:18:47,160 Speaker 1: face that was supposedly neutral, they saw it intercut with 321 00:18:47,359 --> 00:18:50,800 Speaker 1: whatever it was, the soup or the coffin, and they said, Nope, 322 00:18:50,840 --> 00:18:53,920 Speaker 1: there is no emotion on this face. In the soup condition, 323 00:18:54,119 --> 00:18:58,600 Speaker 1: sixty eight percent selected no emotion. In both the child 324 00:18:58,720 --> 00:19:01,720 Speaker 1: and the coffin can s and sixty one percent said 325 00:19:01,800 --> 00:19:05,160 Speaker 1: no emotion, and so comparing that to the control group, 326 00:19:05,680 --> 00:19:08,640 Speaker 1: in the control eight percent said there was no emotion, 327 00:19:08,760 --> 00:19:11,760 Speaker 1: and that dropped down to sixty eight in the soup 328 00:19:12,000 --> 00:19:15,640 Speaker 1: and sixty one in the child and the coffin. So 329 00:19:15,920 --> 00:19:19,080 Speaker 1: you could say this is a small increase in perceived emotion, 330 00:19:19,160 --> 00:19:21,119 Speaker 1: though the authors note that for the size of the 331 00:19:21,119 --> 00:19:24,560 Speaker 1: group they tested, it actually doesn't reach statistical significance, so 332 00:19:24,880 --> 00:19:27,639 Speaker 1: it might just be a random fluke. Furthermore, in the 333 00:19:27,680 --> 00:19:31,639 Speaker 1: cases where the viewers picked in emotion, it was usually 334 00:19:31,840 --> 00:19:35,040 Speaker 1: not the expected emotion, so it was not happiness for 335 00:19:35,080 --> 00:19:38,280 Speaker 1: the child and so forth. So either way, this experiment 336 00:19:38,320 --> 00:19:42,440 Speaker 1: finds something somewhere between no effect and small effect on 337 00:19:42,600 --> 00:19:45,520 Speaker 1: perceived emotion, which is a very far cry either way 338 00:19:45,520 --> 00:19:49,639 Speaker 1: from Kolashov's reports about the audiences unanimous raving about the 339 00:19:49,640 --> 00:19:54,000 Speaker 1: actor's subtle emotional performances, And so the authors say here that, 340 00:19:54,080 --> 00:19:56,960 Speaker 1: you know, in less contrary evidence emerges, it seems true 341 00:19:57,000 --> 00:20:00,600 Speaker 1: to say that quote the Kolashov effect as report did 342 00:20:00,880 --> 00:20:04,040 Speaker 1: no longer exists, even if the effect did play a 343 00:20:04,160 --> 00:20:07,320 Speaker 1: role at one time, though emphasis there should be on 344 00:20:07,440 --> 00:20:10,119 Speaker 1: as reported because some of the broader implications of it 345 00:20:10,160 --> 00:20:14,840 Speaker 1: probably do still hold true. Now, this raises an interesting question. 346 00:20:15,160 --> 00:20:18,159 Speaker 1: If we assume, for the sake of argument, that Kolashev 347 00:20:18,240 --> 00:20:22,520 Speaker 1: was basically reporting the results of his experiment accurately or 348 00:20:22,520 --> 00:20:26,480 Speaker 1: with only slight exaggeration, what could account between the difference. 349 00:20:26,520 --> 00:20:29,640 Speaker 1: Why did Kolashov get people raving about the subtle emotion 350 00:20:29,720 --> 00:20:32,919 Speaker 1: in the neutral face, but that that didn't really happen 351 00:20:32,920 --> 00:20:35,919 Speaker 1: in a modern experiment. The authors offer some ideas here, 352 00:20:35,920 --> 00:20:39,800 Speaker 1: and I think they're all pretty possible, viable, and certainly interesting. 353 00:20:39,920 --> 00:20:44,800 Speaker 1: So one would be changes in audience expectation. You know, 354 00:20:44,880 --> 00:20:48,760 Speaker 1: audiences today are accustomed to highly effective editing techniques that 355 00:20:48,800 --> 00:20:52,200 Speaker 1: have been perfected over time, such as, like I mentioned earlier, 356 00:20:52,200 --> 00:20:56,200 Speaker 1: the preservation of eyelines to enforce continuity of of perspective 357 00:20:56,240 --> 00:20:59,119 Speaker 1: and reverse shots. Yeah, yeah, I think this is this 358 00:20:59,200 --> 00:21:00,680 Speaker 1: is a big one, And I mean it comes down 359 00:21:00,680 --> 00:21:02,440 Speaker 1: to like some of the basics of what we said 360 00:21:02,480 --> 00:21:05,159 Speaker 1: earlier about how at least for many of us and 361 00:21:05,160 --> 00:21:07,800 Speaker 1: certainly for me, like trying to watch an actual Kolashaw 362 00:21:07,920 --> 00:21:11,560 Speaker 1: film is very difficult. Like it's just film has come 363 00:21:12,200 --> 00:21:15,879 Speaker 1: has evolved so much since then, um, and and the 364 00:21:15,920 --> 00:21:19,840 Speaker 1: effects are subtle in a way that you really the 365 00:21:19,960 --> 00:21:23,160 Speaker 1: film only has to be even halfway competent to really 366 00:21:23,200 --> 00:21:26,200 Speaker 1: just draw you in and create the illusion. Right, So, 367 00:21:26,600 --> 00:21:28,720 Speaker 1: uh so the author's right quote. It may be that 368 00:21:28,800 --> 00:21:32,679 Speaker 1: a modern audience, by virtue of increased media exposure relative 369 00:21:32,720 --> 00:21:35,320 Speaker 1: to cool a shows day, has become accustomed to a 370 00:21:35,359 --> 00:21:40,080 Speaker 1: more systematic and complex set of associational cues, such as 371 00:21:40,080 --> 00:21:43,480 Speaker 1: those supplied by the continuity system of editing, and is 372 00:21:43,520 --> 00:21:47,399 Speaker 1: correspondingly less likely to respond to a montage sequence that 373 00:21:47,440 --> 00:21:51,280 Speaker 1: employs a blank face and minimal, if any associative cues 374 00:21:51,320 --> 00:21:56,000 Speaker 1: within shots. So maybe the bar for perceiving emotion in 375 00:21:56,119 --> 00:21:58,879 Speaker 1: films has has gone up, you know, it's just harder 376 00:21:58,920 --> 00:22:02,320 Speaker 1: to do now. And at the time that Kolashov did 377 00:22:02,400 --> 00:22:06,560 Speaker 1: his experiment, allegedly maybe the audiences were just we're just 378 00:22:06,760 --> 00:22:10,320 Speaker 1: more it was easier for them to project to that emotion. 379 00:22:10,960 --> 00:22:12,440 Speaker 1: Now that there could be a number of ways to 380 00:22:12,480 --> 00:22:15,080 Speaker 1: read that. One way is is thinking about how much 381 00:22:15,119 --> 00:22:19,879 Speaker 1: exposure modern audiences have to modern editing techniques. Um. The 382 00:22:20,440 --> 00:22:23,000 Speaker 1: other way, I guess, and the authors don't really favor 383 00:22:23,080 --> 00:22:25,760 Speaker 1: this explanation. They say another way of looking at it 384 00:22:25,840 --> 00:22:29,000 Speaker 1: is naivete on the part of the early audiences. There's 385 00:22:29,000 --> 00:22:32,359 Speaker 1: some kind of projection going on, because maybe early film 386 00:22:32,359 --> 00:22:35,760 Speaker 1: audiences were just so bewildered by moving pictures that they 387 00:22:35,760 --> 00:22:40,480 Speaker 1: almost like hallucinated projections of emotion. Uh. The authors don't 388 00:22:40,480 --> 00:22:43,080 Speaker 1: think this is a very good explanation for one thing, 389 00:22:43,119 --> 00:22:45,960 Speaker 1: because they argue that a lot of the stories that 390 00:22:46,000 --> 00:22:49,240 Speaker 1: are used to to illustrate the sort of bewilderment of 391 00:22:49,280 --> 00:22:52,280 Speaker 1: early film audiences like that, you know, the semi mythological 392 00:22:52,320 --> 00:22:55,320 Speaker 1: things about the audiences running away from the Loomi air 393 00:22:55,359 --> 00:22:58,080 Speaker 1: train and stuff that they say that, I mean, there 394 00:22:58,119 --> 00:23:00,720 Speaker 1: were sort of events of this kind, but they have 395 00:23:00,840 --> 00:23:05,439 Speaker 1: been mythologized in a way that over emphasizes how naive 396 00:23:05,520 --> 00:23:08,160 Speaker 1: early audiences were, and that a lot of these kinds 397 00:23:08,160 --> 00:23:11,200 Speaker 1: of reactions may have just been audiences playing along there 398 00:23:11,200 --> 00:23:13,679 Speaker 1: at the theater, having a good time, and they're playing 399 00:23:13,720 --> 00:23:16,920 Speaker 1: along with what the suggested reaction was supposed to be. 400 00:23:17,280 --> 00:23:19,280 Speaker 1: That's true once you especially when you're dealing with a 401 00:23:19,359 --> 00:23:22,879 Speaker 1: group of people, you know, watching watching anything with a group, 402 00:23:22,920 --> 00:23:25,959 Speaker 1: even even today with our our modern exposure to cinema, 403 00:23:26,480 --> 00:23:28,840 Speaker 1: you know, if one person jumps, everybody can jump. That 404 00:23:28,920 --> 00:23:31,120 Speaker 1: sort of thing, you know, you're more maybe you're more 405 00:23:31,160 --> 00:23:33,520 Speaker 1: likely to to laugh or scream if you're watching it 406 00:23:33,560 --> 00:23:36,600 Speaker 1: with with other people. That sort of thing makes me 407 00:23:36,600 --> 00:23:38,840 Speaker 1: think about William Castle and The Tingler trying to get 408 00:23:38,840 --> 00:23:42,680 Speaker 1: people screaming in the movie theaters. Yeah, yeah, which which 409 00:23:42,760 --> 00:23:46,080 Speaker 1: is uh is infectious. As I think I mentioned in 410 00:23:46,080 --> 00:23:48,960 Speaker 1: that Tingler episode, I got to see The Tingler uh 411 00:23:49,000 --> 00:23:51,800 Speaker 1: in a theater and people were totally playing into it 412 00:23:51,840 --> 00:23:54,800 Speaker 1: like it's still worked today. So good, Okay. A couple 413 00:23:54,800 --> 00:23:58,679 Speaker 1: of other possible explanations for the difference between Kolashov's report 414 00:23:58,720 --> 00:24:00,800 Speaker 1: and then and then they failed to hempt to replicate 415 00:24:00,840 --> 00:24:05,600 Speaker 1: those findings. Another one is response bias. So this seems 416 00:24:05,680 --> 00:24:09,119 Speaker 1: quite possible to me. Maybe it was originally a sloppy experiment. 417 00:24:09,200 --> 00:24:13,280 Speaker 1: Maybe Kolashov primed his test subjects to react the way 418 00:24:13,280 --> 00:24:16,280 Speaker 1: they did, and they complied. Uh. You know that. This 419 00:24:16,320 --> 00:24:18,960 Speaker 1: is why double blind tests are very useful. If the 420 00:24:19,000 --> 00:24:24,200 Speaker 1: person administering the test doesn't know what hypothesis is being tested, 421 00:24:24,760 --> 00:24:26,600 Speaker 1: it's harder for them to behave in a way that 422 00:24:26,640 --> 00:24:30,240 Speaker 1: would bias, that would bias the subject response in favor 423 00:24:30,280 --> 00:24:33,359 Speaker 1: of it. And there is of course extensive evidence that 424 00:24:33,440 --> 00:24:36,960 Speaker 1: Kolashov was already committed to his theory about the power 425 00:24:37,000 --> 00:24:41,040 Speaker 1: of montage before he allegedly conducted this experiment, like he 426 00:24:41,040 --> 00:24:45,560 Speaker 1: he already had the result he was looking for in mind. Yeah, 427 00:24:45,640 --> 00:24:48,880 Speaker 1: like the neutral face. I keep thinking of examples now 428 00:24:48,880 --> 00:24:52,159 Speaker 1: of neutral face or very neutral or or just you know, 429 00:24:52,240 --> 00:24:55,679 Speaker 1: low key acting performances. And one that instantly comes to 430 00:24:55,720 --> 00:24:59,240 Speaker 1: mind is the sequence in The Godfather where al Pacino's 431 00:24:59,320 --> 00:25:04,320 Speaker 1: character is in the restaurant with uh was the corrupt 432 00:25:04,359 --> 00:25:08,399 Speaker 1: police officer and Sterling Hayden and yeah, and the Turk, 433 00:25:08,680 --> 00:25:11,280 Speaker 1: right is that the other character his name also it's 434 00:25:11,280 --> 00:25:14,560 Speaker 1: also um And of course what's gonna happen is he's 435 00:25:14,560 --> 00:25:16,119 Speaker 1: gonna go to the toilet, He's gonna come back with 436 00:25:16,160 --> 00:25:17,800 Speaker 1: a gun, and then He's going to shoot them both. 437 00:25:17,840 --> 00:25:20,320 Speaker 1: That's the plan. And there's that great sequence where you 438 00:25:20,400 --> 00:25:23,040 Speaker 1: see al Pacino's face and he's he had a very again, 439 00:25:23,160 --> 00:25:26,479 Speaker 1: very neutral expression, and I previously just always thought, well, 440 00:25:26,520 --> 00:25:28,800 Speaker 1: that's just he's just he was such a great actor 441 00:25:28,840 --> 00:25:30,919 Speaker 1: at that point in his career, Like like you can 442 00:25:31,000 --> 00:25:33,560 Speaker 1: just see the wheels turning, you can see all the 443 00:25:33,640 --> 00:25:36,600 Speaker 1: tension going on behind the scenes. But maybe not, Maybe 444 00:25:36,640 --> 00:25:39,480 Speaker 1: he's just thinking about, you know what, what the what 445 00:25:39,600 --> 00:25:41,160 Speaker 1: he needs to pick up at the grocery store later 446 00:25:41,240 --> 00:25:43,439 Speaker 1: on in the day, and it's just all about everything 447 00:25:43,520 --> 00:25:45,280 Speaker 1: else going on in the scene and how it's been 448 00:25:45,280 --> 00:25:47,720 Speaker 1: put together that could be there. They're actually a number 449 00:25:47,720 --> 00:25:51,520 Speaker 1: of shots in The Godfather in particular where they're memorable 450 00:25:51,640 --> 00:25:55,800 Speaker 1: because of al Pacino's expressionless face, like when uh, when 451 00:25:55,880 --> 00:25:59,560 Speaker 1: Carlo Ritzie confesses at the end to having killed Sonny 452 00:25:59,720 --> 00:26:02,760 Speaker 1: and and Michael just looks at him with the blank expression. 453 00:26:03,160 --> 00:26:05,879 Speaker 1: But you read a lot into that blank expression. It 454 00:26:06,000 --> 00:26:09,800 Speaker 1: is a murderous blank expression. But there's another way of 455 00:26:09,840 --> 00:26:13,960 Speaker 1: reading the al Pacino example here, and also of possibly 456 00:26:14,200 --> 00:26:18,680 Speaker 1: interpreting the original Mojukan experiment. I really like this explanation. 457 00:26:19,160 --> 00:26:23,240 Speaker 1: What if Kulashev's montage was loaded with more conventional emotional 458 00:26:23,359 --> 00:26:26,640 Speaker 1: content than he claimed. There could be a million ways 459 00:26:26,720 --> 00:26:29,639 Speaker 1: this could be true. But for example, what if there 460 00:26:29,720 --> 00:26:33,959 Speaker 1: was something special about the face of Majukin What if 461 00:26:34,000 --> 00:26:37,640 Speaker 1: there was something special about the face that Kulashev used 462 00:26:37,720 --> 00:26:41,800 Speaker 1: in this supposedly neutral test film there was less neutral 463 00:26:41,880 --> 00:26:44,680 Speaker 1: than we would be led to believe. The authors of 464 00:26:44,760 --> 00:26:47,120 Speaker 1: this ninety two paper note quote, there is a difference 465 00:26:47,200 --> 00:26:52,560 Speaker 1: between an expressionless face and an ambiguous expression. And they 466 00:26:52,600 --> 00:26:55,200 Speaker 1: started an experience from their own experiment. They talked about 467 00:26:55,240 --> 00:26:58,040 Speaker 1: how the very first tape they created, if somebody trying 468 00:26:58,080 --> 00:27:00,879 Speaker 1: to do a neutral face, had to be rejected and 469 00:27:01,000 --> 00:27:04,040 Speaker 1: replaced with a different actor because it failed to be 470 00:27:04,200 --> 00:27:07,119 Speaker 1: rated as neutral in the control condition. So that was 471 00:27:07,160 --> 00:27:10,640 Speaker 1: the control when there were no shots juxtaposed, the control 472 00:27:10,720 --> 00:27:13,720 Speaker 1: group thought they perceived a range of emotions in the 473 00:27:13,800 --> 00:27:16,520 Speaker 1: first neutral face they looked at, and then the author 474 00:27:16,560 --> 00:27:19,320 Speaker 1: has got a different tape, different actor, and it succeeded 475 00:27:19,400 --> 00:27:22,320 Speaker 1: at being perceived as more neutral in the original control. 476 00:27:23,080 --> 00:27:25,000 Speaker 1: This is great to point out, yeah, the difference between 477 00:27:25,400 --> 00:27:29,359 Speaker 1: a neutral face and an ambiguous face, because obviously this 478 00:27:29,520 --> 00:27:32,359 Speaker 1: is one of the arguments for why the Mona Lisa 479 00:27:32,480 --> 00:27:36,400 Speaker 1: by Leonardo da Vinci Is is such a an admired 480 00:27:36,480 --> 00:27:40,119 Speaker 1: piece of art is not because you can easily read 481 00:27:40,640 --> 00:27:44,240 Speaker 1: what the Mona Lisa is um is thinking or feeling, 482 00:27:44,359 --> 00:27:47,680 Speaker 1: but that she has this ambiguous countenance, right, and the 483 00:27:47,720 --> 00:27:49,760 Speaker 1: difference to be that there there is a difference between 484 00:27:49,840 --> 00:27:53,320 Speaker 1: ambiguous and neutral. Neutral is something we look at and 485 00:27:53,359 --> 00:27:55,840 Speaker 1: we see I I don't see any emotion on that face. 486 00:27:56,280 --> 00:28:00,159 Speaker 1: Ambiguous is you see emotion, but it's not clear what 487 00:28:00,280 --> 00:28:02,520 Speaker 1: it is. It maybe suggests something that could go in 488 00:28:02,640 --> 00:28:06,920 Speaker 1: different directions. Oh, but then the authors come back to 489 00:28:07,320 --> 00:28:10,960 Speaker 1: talking about this more ambiguous, more emotional face that they 490 00:28:11,520 --> 00:28:13,560 Speaker 1: got the first time they tried to record a tape, 491 00:28:13,960 --> 00:28:16,520 Speaker 1: They said, quote. When other viewers were shown this face 492 00:28:16,600 --> 00:28:19,879 Speaker 1: and sequence, many attributed a wide range of emotions to 493 00:28:19,960 --> 00:28:23,639 Speaker 1: the actor, some consistent with the cool ashev effect, others not. 494 00:28:24,200 --> 00:28:32,640 Speaker 1: The sequence with the soup, for example, elicited interpretations of apathy, disgust, contemplation, detachment, dislike, indifference, 495 00:28:32,960 --> 00:28:36,240 Speaker 1: lack of interest, as well as an occasional attribution of hunger. 496 00:28:36,920 --> 00:28:40,520 Speaker 1: The ambiguous expression seemed to offer a stronger interpretive cue 497 00:28:40,680 --> 00:28:44,160 Speaker 1: for the viewer than did the expressionless face. If cool 498 00:28:44,200 --> 00:28:47,479 Speaker 1: a Chauvian montage may not be capable of making an 499 00:28:47,560 --> 00:28:51,120 Speaker 1: expressionless face emotive, it may very well do with an 500 00:28:51,240 --> 00:28:55,600 Speaker 1: ambiguous expression, since the objects like soup, coffin, or child 501 00:28:55,960 --> 00:29:00,640 Speaker 1: provide a context for resolving the ambiguity. And I think 502 00:29:00,720 --> 00:29:05,360 Speaker 1: this interpretation seems very likely to me because again, the 503 00:29:05,440 --> 00:29:09,680 Speaker 1: allegation is that Mosuken was a a famed actor, and 504 00:29:10,120 --> 00:29:13,600 Speaker 1: so there's naturally you can imagine a famed actor's face 505 00:29:13,800 --> 00:29:16,920 Speaker 1: has something special about it. It's kind of brimming with 506 00:29:17,360 --> 00:29:20,920 Speaker 1: with the the implication of emotion, even when they're being 507 00:29:21,040 --> 00:29:24,200 Speaker 1: relatively subtle or not, you know, offering a big smile 508 00:29:24,400 --> 00:29:27,640 Speaker 1: or frown or whatever, right, right, that this may well 509 00:29:27,680 --> 00:29:31,360 Speaker 1: have been the sort of performer that was highly aware 510 00:29:31,480 --> 00:29:33,200 Speaker 1: of what their face is doing. That is, you know, 511 00:29:33,320 --> 00:29:36,040 Speaker 1: that is practiced in front of the mirror, that knows 512 00:29:36,120 --> 00:29:39,880 Speaker 1: what they're projecting, and therefore, to you know, to a 513 00:29:39,920 --> 00:29:42,400 Speaker 1: certain instan might be incapable of a neutral face at 514 00:29:42,480 --> 00:29:46,640 Speaker 1: least when when when told to pull some sort of face. Right. So, 515 00:29:46,800 --> 00:29:49,520 Speaker 1: if there's something to this interpretation, I would say that 516 00:29:49,920 --> 00:29:52,360 Speaker 1: that the coolest shof effect, even in the specific case 517 00:29:52,440 --> 00:29:55,680 Speaker 1: of interpreting neutral faces, as you know, based on the 518 00:29:55,960 --> 00:30:00,480 Speaker 1: the editing context, it's absolutely tapping into some thing real, 519 00:30:00,720 --> 00:30:04,400 Speaker 1: but there might be like thresholds or limits, like there 520 00:30:04,560 --> 00:30:06,840 Speaker 1: is some truth to it, but it can't overcome some 521 00:30:07,080 --> 00:30:12,760 Speaker 1: truly deeply blandly neutral faces, you know, like some ambiguous 522 00:30:12,880 --> 00:30:16,960 Speaker 1: faces just offer more hooks on which to hang emotional 523 00:30:17,120 --> 00:30:21,840 Speaker 1: values created by the context. Yeah. Yeah, I also wonder 524 00:30:22,440 --> 00:30:24,440 Speaker 1: what would what would happen if you, you know, it 525 00:30:24,520 --> 00:30:27,000 Speaker 1: took exceptional faces and you threw them in, you know, 526 00:30:27,120 --> 00:30:30,440 Speaker 1: and not necessarily even exceptionally dashing faces, but like just 527 00:30:30,600 --> 00:30:33,080 Speaker 1: exceptionally evocative faces, like like I don't know, like a 528 00:30:33,120 --> 00:30:36,040 Speaker 1: Peter Laurie. You know, if you put Peter Laurie in there, 529 00:30:36,080 --> 00:30:37,720 Speaker 1: just may even you know, even though he's gonna do 530 00:30:37,960 --> 00:30:40,960 Speaker 1: you know, a neutral ambiguous face. Uh, you know, what 531 00:30:41,080 --> 00:30:43,240 Speaker 1: would happen to the experiment? Of course, in that case, 532 00:30:43,280 --> 00:30:45,480 Speaker 1: you'd also have to not know it was Peter Lori, 533 00:30:46,120 --> 00:30:48,719 Speaker 1: because then you're gonna you're gonna start typecasting like, oh, 534 00:30:49,000 --> 00:30:51,000 Speaker 1: we know what kind of guys this this this actor 535 00:30:51,080 --> 00:30:55,000 Speaker 1: plays you'd be suspicious, you'd be reading negative emotional or 536 00:30:55,400 --> 00:30:58,560 Speaker 1: suspicious mind content. What is the planning for that soup. 537 00:30:58,640 --> 00:31:01,880 Speaker 1: He's going to poison that soup any right, anyway, I 538 00:31:01,960 --> 00:31:03,600 Speaker 1: think the authors make the point in the end that 539 00:31:03,680 --> 00:31:06,840 Speaker 1: the the broader implications of the cool ashav myth that 540 00:31:07,040 --> 00:31:10,640 Speaker 1: that individual shots, which may be low on meaning or 541 00:31:10,720 --> 00:31:14,440 Speaker 1: emotion by themselves, can become highly charged with meaning by 542 00:31:14,480 --> 00:31:17,800 Speaker 1: the power of the surrounding editing. This is obviously true, 543 00:31:18,000 --> 00:31:21,400 Speaker 1: and it is largely the basis for the magic of cinema. 544 00:31:22,080 --> 00:31:25,920 Speaker 1: But the specific claim about supposedly neutral faces appears to 545 00:31:26,000 --> 00:31:29,880 Speaker 1: be not true, at least for some audiences or some faces. 546 00:31:30,560 --> 00:31:33,800 Speaker 1: But this raises really interesting questions like, what are the 547 00:31:33,880 --> 00:31:38,200 Speaker 1: properties of the maximally cool a shov ambiguous face? You know, what, 548 00:31:38,640 --> 00:31:40,760 Speaker 1: what kind of skills would you want an actor to 549 00:31:40,920 --> 00:31:44,959 Speaker 1: have to be able to have these you know, subtle 550 00:31:45,040 --> 00:31:50,120 Speaker 1: ambiguous expressions that can be sort of driven any which 551 00:31:50,160 --> 00:31:53,080 Speaker 1: way by the surrounding context, by a bowl of soup 552 00:31:53,200 --> 00:31:55,600 Speaker 1: or by a coffin. I guess, you know, I'm just 553 00:31:55,840 --> 00:31:58,160 Speaker 1: guessing here, But the bare minimum you need to have 554 00:31:58,320 --> 00:32:00,360 Speaker 1: some sort of like spark of at ten ship. Like 555 00:32:00,440 --> 00:32:04,120 Speaker 1: they're saying, it's not not enough perhaps to just rely 556 00:32:04,720 --> 00:32:07,440 Speaker 1: solely on the editing to imply that there's a connection 557 00:32:07,480 --> 00:32:10,200 Speaker 1: between this shot and the other. But the person's face 558 00:32:10,680 --> 00:32:14,000 Speaker 1: appears to be looking with interest at something, you know. Yeah, 559 00:32:14,320 --> 00:32:16,320 Speaker 1: that's that's a good point. I mean, I think sometimes 560 00:32:16,360 --> 00:32:19,880 Speaker 1: with these studies, like the face doesn't just look neutral. 561 00:32:20,000 --> 00:32:23,360 Speaker 1: It looks like it's not seeing anything, right, Like if 562 00:32:23,400 --> 00:32:26,320 Speaker 1: it's just like mug shot and then and then pick 563 00:32:26,400 --> 00:32:28,360 Speaker 1: a plate of spaghetti, Like, okay, you show me a 564 00:32:28,400 --> 00:32:30,880 Speaker 1: mug shot and you show me some spaghetti. Maybe something 565 00:32:30,960 --> 00:32:34,440 Speaker 1: that's crucial is that even if they're not showing a 566 00:32:34,600 --> 00:32:38,000 Speaker 1: very clear emotion, that it looks like they're looking at 567 00:32:38,160 --> 00:32:49,360 Speaker 1: whatever is being shown. Yeah, So Princeton Henley is very interesting, 568 00:32:49,520 --> 00:32:52,400 Speaker 1: but it was by no means the last study on 569 00:32:52,560 --> 00:32:54,600 Speaker 1: the cooler Shop effect, the last attempt to look at 570 00:32:54,640 --> 00:32:58,120 Speaker 1: it empirically, And actually since then some other studies have 571 00:32:58,240 --> 00:33:00,520 Speaker 1: kind of come back on the other side found a 572 00:33:00,600 --> 00:33:05,360 Speaker 1: little more support for the original alleged finding. So one 573 00:33:05,440 --> 00:33:09,800 Speaker 1: example is the is the study by Dean mobs at 574 00:33:09,840 --> 00:33:13,200 Speaker 1: All from two thousand six called the Coolest shov Effect 575 00:33:13,360 --> 00:33:17,040 Speaker 1: the Influence of contextual framing on emotional attributions. This was 576 00:33:17,120 --> 00:33:20,840 Speaker 1: in Social Cognitive and Effective Neuroscience, and the test here 577 00:33:20,920 --> 00:33:23,960 Speaker 1: was a little bit different, but they did basically look 578 00:33:24,040 --> 00:33:26,840 Speaker 1: for the same type of effect and did succeed in 579 00:33:26,960 --> 00:33:30,560 Speaker 1: producing it experimentally. So in this case, they didn't use 580 00:33:30,920 --> 00:33:35,880 Speaker 1: just a single supposedly neutral face as the stimulus. They 581 00:33:36,040 --> 00:33:39,360 Speaker 1: used neutral faces and then what they called faces displaying 582 00:33:39,560 --> 00:33:44,440 Speaker 1: subtly fearful or happy facial expressions, which if you want 583 00:33:44,480 --> 00:33:46,280 Speaker 1: to look up the study you can see the stimuli 584 00:33:46,360 --> 00:33:49,640 Speaker 1: they use the yeah, they're they're play their faces that 585 00:33:49,720 --> 00:33:53,080 Speaker 1: are almost neutral. They've just got the barest little hint 586 00:33:53,160 --> 00:33:56,280 Speaker 1: of a smile or kind of an apprehensive frown. And 587 00:33:56,320 --> 00:33:58,800 Speaker 1: then they put together a task where they would actually 588 00:33:58,800 --> 00:34:01,760 Speaker 1: they paired it with neuroimaging in the study, so they 589 00:34:01,880 --> 00:34:05,320 Speaker 1: have people doing neuroimaging while they gave them the task 590 00:34:05,440 --> 00:34:08,320 Speaker 1: to look at this face and then imagine that the 591 00:34:08,400 --> 00:34:11,640 Speaker 1: person is watching a movie of various kinds. It could 592 00:34:11,680 --> 00:34:15,200 Speaker 1: be a happy movie scene or a scary movie scene. Uh. 593 00:34:15,400 --> 00:34:18,359 Speaker 1: And they did find that people were on average more 594 00:34:18,520 --> 00:34:22,640 Speaker 1: likely to interpret neutral or only very subtle expressive faces 595 00:34:23,200 --> 00:34:25,760 Speaker 1: more in alignment with the emotion that you would expect 596 00:34:25,920 --> 00:34:28,880 Speaker 1: if they believed the person was watching either a scary 597 00:34:29,000 --> 00:34:31,239 Speaker 1: or a happy movie. And so it's worth noting that 598 00:34:31,320 --> 00:34:34,120 Speaker 1: there is an effect here, but it's not as shockingly 599 00:34:34,239 --> 00:34:37,520 Speaker 1: powerful and unanimous as like those original tellings of the 600 00:34:37,760 --> 00:34:42,760 Speaker 1: Kolershov experiment would suggest. Mm hmm, yeah, this is interesting 601 00:34:42,840 --> 00:34:44,919 Speaker 1: with its something we'll continue to look at. I also 602 00:34:45,040 --> 00:34:48,240 Speaker 1: like that they were looking at scary and happy movie 603 00:34:48,280 --> 00:34:52,719 Speaker 1: scenes because it also brings to mind episodes we've done 604 00:34:52,760 --> 00:34:57,000 Speaker 1: in the past on audience reactions too scary movies and 605 00:34:57,120 --> 00:35:00,320 Speaker 1: how oftentimes like like the the reaction and you have 606 00:35:00,520 --> 00:35:05,120 Speaker 1: to a pleasant movie or certainly a funny movie compared 607 00:35:05,160 --> 00:35:07,200 Speaker 1: to that of a scary movie. Uh, that they may 608 00:35:07,520 --> 00:35:10,560 Speaker 1: be more like than one might think. Oh yeah, because 609 00:35:10,600 --> 00:35:15,040 Speaker 1: a lot of times people laugh when something is scary. Yeah, laughing, Uh, 610 00:35:15,280 --> 00:35:17,480 Speaker 1: you know, reacting to the way that people around them 611 00:35:17,520 --> 00:35:20,520 Speaker 1: are reacting. And if you are acting frightened during a 612 00:35:20,640 --> 00:35:23,239 Speaker 1: frightening movie, it's I feel like it's very often a 613 00:35:23,320 --> 00:35:25,719 Speaker 1: kind of excited frightening, you know, that's safe kind of 614 00:35:25,920 --> 00:35:28,080 Speaker 1: like I am. I am afraid for the characters, but 615 00:35:28,160 --> 00:35:31,240 Speaker 1: I'm not necessarily afraid for myself. You know, I've actually 616 00:35:31,320 --> 00:35:34,839 Speaker 1: wondered before if so. A lot of my movie going 617 00:35:35,000 --> 00:35:39,239 Speaker 1: entertainment pleasure comes from watching be horror movies. Essentially as 618 00:35:39,400 --> 00:35:43,720 Speaker 1: unintentional comedies and having a good time laughing, laughing along 619 00:35:43,800 --> 00:35:46,920 Speaker 1: with them. But I wonder if part of that grows 620 00:35:46,960 --> 00:35:49,680 Speaker 1: out of a kind of defense mechanism learned in childhood, 621 00:35:49,800 --> 00:35:53,319 Speaker 1: that that I could protect myself from something scary if 622 00:35:53,360 --> 00:35:56,480 Speaker 1: I sort of forced myself to see it instead as 623 00:35:56,560 --> 00:35:59,799 Speaker 1: something funny. Yeah. I don't know. I I certainly catch 624 00:35:59,840 --> 00:36:04,920 Speaker 1: my self going like, ah, more like that exact um 625 00:36:05,520 --> 00:36:09,080 Speaker 1: sound if it is say a slightly goofy or goofy 626 00:36:09,200 --> 00:36:12,440 Speaker 1: monster that is suddenly jumping out as opposed to a 627 00:36:12,560 --> 00:36:17,960 Speaker 1: more I don't know, effective looking special effect. Uh, there's 628 00:36:18,000 --> 00:36:20,719 Speaker 1: something about I don't know, it's probably you know, all 629 00:36:20,760 --> 00:36:23,640 Speaker 1: this is highly subjective, but for me at least, uh, 630 00:36:23,880 --> 00:36:26,560 Speaker 1: you know, maybe I'm just leaning into the imagination more 631 00:36:26,680 --> 00:36:29,640 Speaker 1: in those cases. Now, Just very briefly, I wanted to 632 00:36:30,320 --> 00:36:32,400 Speaker 1: point out a couple more studies I dug up that 633 00:36:32,560 --> 00:36:35,359 Speaker 1: looked into the cooler Shov effect more recently than this one. 634 00:36:35,520 --> 00:36:38,600 Speaker 1: So there was a study in the journal Perception in 635 00:36:38,680 --> 00:36:41,920 Speaker 1: two thousand and sixteen by Daniel Barrett at All called 636 00:36:42,400 --> 00:36:45,400 Speaker 1: does the cool Shov Effect Really Exist? Revisiting a classic 637 00:36:45,440 --> 00:36:50,560 Speaker 1: film experiment on facial expressions and emotional context. So they 638 00:36:50,640 --> 00:36:52,600 Speaker 1: note some of the stuff we already did, doubts about 639 00:36:52,600 --> 00:36:56,160 Speaker 1: the original experiment, and then the fact that recent attempts 640 00:36:56,239 --> 00:37:00,440 Speaker 1: to reproduce the effect have had conflicting results. So tried 641 00:37:00,480 --> 00:37:03,359 Speaker 1: it out with a group of thirty six participants who 642 00:37:03,400 --> 00:37:08,400 Speaker 1: were presented with twenty four film sequences of neutral faces 643 00:37:08,600 --> 00:37:12,440 Speaker 1: across six different emotional conditions, so trying to reproduce the 644 00:37:12,520 --> 00:37:15,719 Speaker 1: same effect, and they actually did find a correlation. It 645 00:37:15,800 --> 00:37:18,040 Speaker 1: may it may not have been huge, but they said 646 00:37:18,120 --> 00:37:21,680 Speaker 1: quote for each emotional condition, the participants tended to choose 647 00:37:21,719 --> 00:37:26,240 Speaker 1: the appropriate the appropriate category more frequently than alternative options, 648 00:37:26,640 --> 00:37:29,479 Speaker 1: while the answers to the valence and arousal questions also 649 00:37:29,600 --> 00:37:32,520 Speaker 1: went in the expected direction. So they did find a 650 00:37:32,640 --> 00:37:36,360 Speaker 1: mild existence of the cool Ashov effect in their research 651 00:37:36,440 --> 00:37:39,759 Speaker 1: here and then there was another one by Baranowski and 652 00:37:39,920 --> 00:37:44,080 Speaker 1: Hate in UH Perception in two thousand seventeen called the 653 00:37:44,160 --> 00:37:48,840 Speaker 1: auditory cool Ashov effect Multisensory integration and movie editing. The 654 00:37:48,920 --> 00:37:50,880 Speaker 1: study tried to see if there were any cool A 655 00:37:50,920 --> 00:37:54,480 Speaker 1: Show type effects, not for cross cutting with visual images, 656 00:37:54,600 --> 00:37:58,200 Speaker 1: but for music. So the question is does music affect 657 00:37:58,719 --> 00:38:03,200 Speaker 1: what emotions people detect? On other people's supposedly neutral faces, 658 00:38:03,760 --> 00:38:06,440 Speaker 1: and according to the authors of this study, their results 659 00:38:06,480 --> 00:38:09,600 Speaker 1: were Yes. They found that sad music did in fact 660 00:38:09,719 --> 00:38:13,319 Speaker 1: make people more likely to rate a supposedly neutral face 661 00:38:13,400 --> 00:38:17,360 Speaker 1: as sad and vice versa. Well that that that doesn't 662 00:38:17,400 --> 00:38:20,839 Speaker 1: surprise me at all. I mean, music, especially music and film, 663 00:38:20,920 --> 00:38:25,080 Speaker 1: is highly manipulative at times. And uh, and I think 664 00:38:25,120 --> 00:38:27,759 Speaker 1: we've all seen experiments with this sort of amateur experiments 665 00:38:27,800 --> 00:38:32,279 Speaker 1: with this online where you take, um, Johnny Cash is 666 00:38:32,680 --> 00:38:34,360 Speaker 1: cover of nine inch Nails Hurt, and you play it 667 00:38:34,400 --> 00:38:38,600 Speaker 1: in the background of virtual virtually any uh neutrals or 668 00:38:38,920 --> 00:38:41,680 Speaker 1: ambiguous footage, and you're going to get a sense of 669 00:38:41,800 --> 00:38:46,200 Speaker 1: like deep personal anguish and and hurt. I'm just I'm 670 00:38:46,239 --> 00:38:47,960 Speaker 1: just putting it all together in my mind right now. 671 00:38:48,000 --> 00:38:52,000 Speaker 1: I'm seeing I'm seeing clips from like Happy Gilmore or something, 672 00:38:52,280 --> 00:38:55,520 Speaker 1: but with with the Johnny Cash, Yeah, to see if 673 00:38:55,560 --> 00:38:58,839 Speaker 1: I still feel. And then finally, one last one. There 674 00:38:58,960 --> 00:39:02,880 Speaker 1: was a paper by mullinicks at All from twenty nineteen 675 00:39:02,960 --> 00:39:05,279 Speaker 1: in pl Os one that also looked at the cool 676 00:39:05,320 --> 00:39:08,480 Speaker 1: Ashov effect, trying to see if it existed for still 677 00:39:08,600 --> 00:39:14,200 Speaker 1: photographs instead of dynamic film sequences, and the authors say, yes, 678 00:39:14,600 --> 00:39:17,000 Speaker 1: they did the cool a Shov type experiment, but just 679 00:39:17,120 --> 00:39:19,480 Speaker 1: with still photos, and they found there was in fact 680 00:39:19,560 --> 00:39:23,240 Speaker 1: a kool Ashov type effect for just for still images. Okay, 681 00:39:23,520 --> 00:39:27,360 Speaker 1: also not surprising to me anyway. So it looks like 682 00:39:27,520 --> 00:39:30,440 Speaker 1: more of the recent studies into this have found some 683 00:39:30,719 --> 00:39:33,200 Speaker 1: kind of effect, though I think sometimes the effects are, 684 00:39:33,560 --> 00:39:35,279 Speaker 1: you know, the kinds of things you're more likely to 685 00:39:35,360 --> 00:39:38,359 Speaker 1: normally see in psychology experiments, kind of modest effects, rather 686 00:39:38,480 --> 00:39:43,240 Speaker 1: than the overwhelming unanimous effect described in the the original 687 00:39:43,320 --> 00:39:47,279 Speaker 1: Masoukan experiment. Now, I'd like to take um all these 688 00:39:47,320 --> 00:39:50,400 Speaker 1: points we've been hitting and come back around to something 689 00:39:50,520 --> 00:39:54,320 Speaker 1: that I briefly discussed, and that was Leonardo da Vinci's 690 00:39:54,320 --> 00:39:57,120 Speaker 1: famous sixteenth century painting The Mona Lisa. One of the 691 00:39:57,160 --> 00:40:01,600 Speaker 1: most intriguing aspects of this painting is the the ultimate 692 00:40:01,800 --> 00:40:04,960 Speaker 1: ambiguity of the expression, you know, the Mona Lisa smile, 693 00:40:05,160 --> 00:40:08,880 Speaker 1: especially Uh, it's a it's a it's it's a slight smile. 694 00:40:09,080 --> 00:40:11,560 Speaker 1: It's a kind of an ambiguous smile. What is she 695 00:40:11,640 --> 00:40:15,560 Speaker 1: smiling about or beginning to smile about? Um? You know 696 00:40:15,640 --> 00:40:18,000 Speaker 1: there there there have been a number of papers written 697 00:40:18,000 --> 00:40:19,520 Speaker 1: about this, and certainly not going to do them all 698 00:40:19,640 --> 00:40:23,160 Speaker 1: justice here, but I wanted to touch on some findings 699 00:40:23,200 --> 00:40:27,440 Speaker 1: that I think can potentially contribute to this conversation. Now, wait, 700 00:40:27,520 --> 00:40:30,680 Speaker 1: did this originally come up in our making a distinction 701 00:40:30,800 --> 00:40:34,600 Speaker 1: between neutrality and ambiguity and so so that maybe you're 702 00:40:34,640 --> 00:40:37,200 Speaker 1: suggesting that the Mona Lisa's face might be one of 703 00:40:37,320 --> 00:40:41,799 Speaker 1: those famous faces that is ambiguous but not neutral. Right, 704 00:40:41,920 --> 00:40:44,800 Speaker 1: it doesn't look like a death mask, but also you 705 00:40:44,840 --> 00:40:47,759 Speaker 1: know she's not She's not scowling, she doesn't look like 706 00:40:48,320 --> 00:40:51,799 Speaker 1: Vigo the copathion. She's not smiling ear to ear. It's 707 00:40:51,840 --> 00:40:56,560 Speaker 1: a very interesting expression, to say the least. Um that 708 00:40:56,719 --> 00:41:00,720 Speaker 1: people have been discussing and studying for for for decades 709 00:41:00,760 --> 00:41:04,120 Speaker 1: and for for for ages. Uh So I'm not going 710 00:41:04,160 --> 00:41:06,120 Speaker 1: to cover all the studies, but there there've been There 711 00:41:06,120 --> 00:41:08,799 Speaker 1: have been plenty, but I was looking at one. Uh. 712 00:41:09,160 --> 00:41:11,760 Speaker 1: This was a theory that was put forth by Professor 713 00:41:11,840 --> 00:41:18,640 Speaker 1: Margaret Livingstone of Harvard University. UM. She argues that, UM, 714 00:41:19,400 --> 00:41:22,840 Speaker 1: a lot of what fascinates us about this painting is 715 00:41:22,880 --> 00:41:27,160 Speaker 1: because the smile appears differently depending on where you're standing 716 00:41:27,280 --> 00:41:30,359 Speaker 1: in position to the painting. So if you look at 717 00:41:30,440 --> 00:41:35,160 Speaker 1: it with your fobial or direct vision. Uh, then arguably 718 00:41:35,440 --> 00:41:37,880 Speaker 1: there's not really a smile going on there. But if 719 00:41:37,920 --> 00:41:41,560 Speaker 1: you view it from your with your peripheral vision, out 720 00:41:41,600 --> 00:41:43,960 Speaker 1: of the corner of your eye, then it seems like 721 00:41:44,000 --> 00:41:47,319 Speaker 1: there's a pronounced smile. Now this doesn't this this little 722 00:41:47,360 --> 00:41:51,919 Speaker 1: tidbit doesn't particularly have a lot to reveal um about 723 00:41:51,960 --> 00:41:53,800 Speaker 1: the broader topic we're discussing here, but I found it 724 00:41:53,840 --> 00:41:56,360 Speaker 1: interesting just talking. And indeed it's one that you can 725 00:41:56,440 --> 00:41:58,040 Speaker 1: You can pull up an image of the Mona Lisa 726 00:41:58,840 --> 00:42:01,320 Speaker 1: on your computer, your phone, own, or if you have 727 00:42:01,440 --> 00:42:04,480 Speaker 1: a copy hanging in your your your house. You can 728 00:42:04,600 --> 00:42:07,360 Speaker 1: do it this way as well, and you'll find I 729 00:42:07,480 --> 00:42:09,640 Speaker 1: think that you do get this effect. If you kind 730 00:42:09,640 --> 00:42:10,799 Speaker 1: of look at out at the corner of your eyes, 731 00:42:10,800 --> 00:42:13,520 Speaker 1: it seems like there's a pronounced smile. Look at her directly, 732 00:42:14,120 --> 00:42:17,120 Speaker 1: and uh, it's it's not there. I see exactly what 733 00:42:17,280 --> 00:42:21,240 Speaker 1: you mean. Another interesting thing is that my mental image 734 00:42:21,280 --> 00:42:25,000 Speaker 1: of the Mona Lisa is smiling more than the actual 735 00:42:25,160 --> 00:42:27,799 Speaker 1: image seems to be when I look at it. Yeah, 736 00:42:28,360 --> 00:42:31,880 Speaker 1: something about the lower resolution copy in my brain appears 737 00:42:31,920 --> 00:42:35,680 Speaker 1: to have accentuated the smile, and maybe somehow that's picking 738 00:42:35,800 --> 00:42:39,560 Speaker 1: up on the kind of subtle shading of the contours 739 00:42:39,640 --> 00:42:42,680 Speaker 1: of her cheeks which looks like they could be continuing 740 00:42:42,800 --> 00:42:46,680 Speaker 1: the lines of her mouth, but it's not her mouth. Yeah, yeah, 741 00:42:47,360 --> 00:42:49,880 Speaker 1: so yeah, I think that that's that's very much it. 742 00:42:49,920 --> 00:42:51,719 Speaker 1: And of course you can get into deeper discussions of 743 00:42:52,000 --> 00:42:54,400 Speaker 1: you know, to what extent um, you know this is 744 00:42:54,480 --> 00:42:56,840 Speaker 1: intended and you know what Leonardo Evin she's trying to 745 00:42:56,920 --> 00:43:00,960 Speaker 1: do with this, um because another another aspect of the 746 00:43:00,960 --> 00:43:03,920 Speaker 1: smile that's frequently brought up is that it's um uh, 747 00:43:04,440 --> 00:43:07,320 Speaker 1: it's it's not a symmetrical smile um. And this is 748 00:43:07,400 --> 00:43:11,799 Speaker 1: often cited as is one of the key interesting aspects 749 00:43:12,000 --> 00:43:17,279 Speaker 1: of the Mona Lisa's smile, of Mona Lisa's face in general, um. Now, 750 00:43:17,760 --> 00:43:20,960 Speaker 1: the emotional impact of her expression has been much debated 751 00:43:21,040 --> 00:43:23,000 Speaker 1: over the years. And he is like like a lot 752 00:43:23,040 --> 00:43:26,480 Speaker 1: of what we discussed in part one and in this episode. 753 00:43:26,680 --> 00:43:28,359 Speaker 1: It's one of those areas where you can you can 754 00:43:28,440 --> 00:43:31,120 Speaker 1: science it all day, but you're still working with subjective 755 00:43:31,239 --> 00:43:34,720 Speaker 1: art rather than objective principles. But there are some papers 756 00:43:34,760 --> 00:43:37,719 Speaker 1: that I think have some revealing information based generally on 757 00:43:37,840 --> 00:43:41,160 Speaker 1: you know, smallish studies uh looking at asking people to 758 00:43:41,280 --> 00:43:44,800 Speaker 1: look at the painting, or look at portions of the 759 00:43:44,840 --> 00:43:48,200 Speaker 1: paintings sometimes they've been manipulated in a key way, and 760 00:43:48,360 --> 00:43:50,360 Speaker 1: see what people have to say about it. And this 761 00:43:50,440 --> 00:43:52,560 Speaker 1: is where we're getting, uh, you know, we're getting into 762 00:43:53,239 --> 00:43:56,279 Speaker 1: something that's more in line with the broader topic here. 763 00:43:56,960 --> 00:43:59,360 Speaker 1: When you look at the Mona Lisa, what kind of 764 00:43:59,480 --> 00:44:05,080 Speaker 1: emotion all um understanding is passing between the painting and yourself? 765 00:44:05,440 --> 00:44:07,799 Speaker 1: Does it depend on what painting is across the room 766 00:44:07,880 --> 00:44:09,879 Speaker 1: from her on the other wall, so like what you're 767 00:44:09,920 --> 00:44:13,000 Speaker 1: perceiving her to be looking at. They didn't get into that, 768 00:44:13,280 --> 00:44:15,880 Speaker 1: uh as much, but I couldn't help but think of it. 769 00:44:15,960 --> 00:44:18,239 Speaker 1: I kept thinking of her looking at soup and so forth. 770 00:44:20,520 --> 00:44:22,200 Speaker 1: But you know, one paper I was looking at was 771 00:44:22,239 --> 00:44:26,680 Speaker 1: a twenty nineteen paper from Marsilli at All published in Cortex, 772 00:44:26,760 --> 00:44:30,359 Speaker 1: the journal Cortex, in which the researchers asked forty two 773 00:44:30,400 --> 00:44:33,520 Speaker 1: individuals to rate which of the six basic emotions as 774 00:44:33,560 --> 00:44:37,200 Speaker 1: well as a neutral expression of emotion was related in 775 00:44:37,600 --> 00:44:42,200 Speaker 1: chimerical images, uh constructed from the photos. So chimerical images 776 00:44:42,280 --> 00:44:45,800 Speaker 1: in this sense are formed from opposing halves of a 777 00:44:46,000 --> 00:44:50,640 Speaker 1: pair of same or different faces, usually in like studies 778 00:44:50,680 --> 00:44:52,400 Speaker 1: and courtroom settings. But in this case it would be 779 00:44:52,480 --> 00:44:55,000 Speaker 1: like you know, um, my understanding here is like mirroring 780 00:44:55,080 --> 00:44:58,600 Speaker 1: different parts of the face, stealing with the with the asymmetry. 781 00:44:58,680 --> 00:45:01,840 Speaker 1: You know, like what if you had side A is 782 00:45:01,920 --> 00:45:04,600 Speaker 1: the and you just cloned it onto side be that 783 00:45:04,680 --> 00:45:07,440 Speaker 1: sort of thing. Now, The results in this case indicated 784 00:45:07,520 --> 00:45:11,279 Speaker 1: that happiness is expressed only on the left side of 785 00:45:11,560 --> 00:45:15,239 Speaker 1: Mona Lisa's face, not on the right. Uh. And this 786 00:45:15,440 --> 00:45:18,280 Speaker 1: actually leans into the interpretation that the Mona Lisa's smile 787 00:45:18,440 --> 00:45:21,799 Speaker 1: is not a legitimate smile at all, but a fake smile, uh, 788 00:45:21,920 --> 00:45:24,640 Speaker 1: something that is either you know, a noteworthy subject of 789 00:45:24,760 --> 00:45:26,320 Speaker 1: of the art in and of itself, or has a 790 00:45:26,360 --> 00:45:29,919 Speaker 1: more specific, even cryptic purpose in da Vinci's art here, 791 00:45:30,680 --> 00:45:33,919 Speaker 1: But and I think potentially makes it more interesting. Peace 792 00:45:34,120 --> 00:45:36,040 Speaker 1: it's not of just a painting of a woman smiling, 793 00:45:36,080 --> 00:45:39,680 Speaker 1: It's a painting of a woman pretending to smile faintly. 794 00:45:40,520 --> 00:45:43,000 Speaker 1: This is interesting because I know that's something I've read, 795 00:45:43,120 --> 00:45:45,040 Speaker 1: and I don't know how legitimate this is, but I've 796 00:45:45,160 --> 00:45:50,000 Speaker 1: I've at least read um facial expression ambiguity as one 797 00:45:50,120 --> 00:45:53,960 Speaker 1: of the features people use to detect fakeery of emotions 798 00:45:54,000 --> 00:45:56,640 Speaker 1: in others. So when people look at somebody else and 799 00:45:56,719 --> 00:46:00,239 Speaker 1: they see that their smile is asymmetrical, they're more likely 800 00:46:00,320 --> 00:46:03,840 Speaker 1: to think they're faking it, right right, Um, And this 801 00:46:04,000 --> 00:46:05,719 Speaker 1: is a topic we've we've covered on the show before 802 00:46:05,760 --> 00:46:08,640 Speaker 1: because you get into that whole topic of of micro 803 00:46:08,800 --> 00:46:13,440 Speaker 1: expressions and reading micro expressions and uh, the the idea 804 00:46:13,560 --> 00:46:16,880 Speaker 1: that that a fake smile looks one way, but there's 805 00:46:16,920 --> 00:46:23,080 Speaker 1: a more profound pronounced um muscle definition to a legitimate smile. 806 00:46:23,680 --> 00:46:25,319 Speaker 1: And so that's, I mean, that's on it on its 807 00:46:25,360 --> 00:46:27,880 Speaker 1: own is something we might take into account when considering 808 00:46:28,520 --> 00:46:34,719 Speaker 1: ambiguous like semi happy, semi smiling, ambiguous um images, and 809 00:46:35,040 --> 00:46:39,280 Speaker 1: ambiguous faces used in one of these experiments. Now, another 810 00:46:39,600 --> 00:46:42,480 Speaker 1: study I looked at here was one from seventeen by 811 00:46:42,640 --> 00:46:47,239 Speaker 1: leacci at All published in Scientific Reports. The researchers here 812 00:46:47,719 --> 00:46:51,560 Speaker 1: manipulated this one's actually kind of funny, I think, manipulated 813 00:46:51,719 --> 00:46:55,800 Speaker 1: Mona Lisa's mouth curvature, uh, and studied how a range 814 00:46:55,880 --> 00:47:02,120 Speaker 1: of happier and sadder face variance influenced perception of her emotions. So, um, 815 00:47:03,040 --> 00:47:04,960 Speaker 1: the actual paper gets into a lot of like they 816 00:47:05,040 --> 00:47:07,640 Speaker 1: bust out some equations in math on this, but basically 817 00:47:07,680 --> 00:47:10,000 Speaker 1: they're just doing what you're imagining now, like making the 818 00:47:10,080 --> 00:47:14,400 Speaker 1: smile more pronounced or making it less pronounced. And um, 819 00:47:14,960 --> 00:47:18,560 Speaker 1: they were able to manipulate perception along a sadness, happiness 820 00:47:18,760 --> 00:47:23,360 Speaker 1: um uh spectrum, but contended ultimately that their data indicates 821 00:47:23,400 --> 00:47:26,800 Speaker 1: that the natural mona Lisa, at any rate, is always happy. 822 00:47:27,480 --> 00:47:30,840 Speaker 1: But I found this more telling quote observers recognize positive 823 00:47:30,920 --> 00:47:35,840 Speaker 1: facial expressions faster than negative expressions. Uh. This is not 824 00:47:35,960 --> 00:47:39,680 Speaker 1: a finding, but just a reality that they were discussing 825 00:47:39,840 --> 00:47:43,440 Speaker 1: in in the paper. So in other words, faces spiraling 826 00:47:43,600 --> 00:47:48,280 Speaker 1: down through neutrality, ambiguity and into other emotional states require 827 00:47:48,400 --> 00:47:52,400 Speaker 1: more contemplation. Uh. And and I'm making assumptions here, but 828 00:47:52,760 --> 00:47:56,239 Speaker 1: but more nuance. So like the like the face that's 829 00:47:56,239 --> 00:47:59,160 Speaker 1: smiling ear to ear or is in a you know, 830 00:47:59,280 --> 00:48:02,200 Speaker 1: the vego the copatheon scowl. We don't have to think 831 00:48:02,360 --> 00:48:04,480 Speaker 1: long and hard about that, Like what kind of emotion 832 00:48:04,760 --> 00:48:07,560 Speaker 1: is this person having about the soup. We know that 833 00:48:07,680 --> 00:48:10,239 Speaker 1: they they're either ecstatic over the soup or they just 834 00:48:10,360 --> 00:48:12,960 Speaker 1: hate the soup or something involved with the soup. We 835 00:48:13,040 --> 00:48:14,920 Speaker 1: don't have to, uh to think about it much. But 836 00:48:15,040 --> 00:48:18,680 Speaker 1: when you have that that that ambiguous smile or even 837 00:48:18,760 --> 00:48:22,319 Speaker 1: a slight uh frown. You know, that's that's when that's 838 00:48:22,320 --> 00:48:24,920 Speaker 1: when that really makes you think, like what is this 839 00:48:25,080 --> 00:48:28,279 Speaker 1: person thinking? My my theory of mind has to maybe 840 00:48:28,400 --> 00:48:30,560 Speaker 1: engage more to try and figure it out, and then 841 00:48:30,640 --> 00:48:32,520 Speaker 1: ultimately we have to remember, I mean, one of the 842 00:48:32,600 --> 00:48:36,120 Speaker 1: key things about people's faces is that the face itself 843 00:48:36,280 --> 00:48:39,080 Speaker 1: is a communication array. So like we're trying to get 844 00:48:39,200 --> 00:48:43,840 Speaker 1: information potentially about that soup, right, like like that this 845 00:48:44,040 --> 00:48:46,520 Speaker 1: individual might know of that soup is good. I want 846 00:48:46,520 --> 00:48:48,920 Speaker 1: to know, like what the inside track is on the 847 00:48:49,000 --> 00:48:53,600 Speaker 1: soup um or on other human beings before I myself 848 00:48:53,680 --> 00:48:55,800 Speaker 1: decide how I feel about it. I know this is 849 00:48:55,840 --> 00:48:57,960 Speaker 1: sort of besides your main point, but it also makes 850 00:48:58,000 --> 00:49:01,719 Speaker 1: me think about the strange biologic contingency that one of 851 00:49:01,760 --> 00:49:04,879 Speaker 1: the main features of that communication arrays also the whole 852 00:49:05,120 --> 00:49:09,080 Speaker 1: that soup goes in. It's true, do you ever think 853 00:49:09,080 --> 00:49:10,960 Speaker 1: about how weird that is? You know, didn't have to 854 00:49:11,000 --> 00:49:13,040 Speaker 1: be that way, but we just we we cram in, 855 00:49:13,840 --> 00:49:16,719 Speaker 1: we cram in nutrition and speak through the same orifice. 856 00:49:17,000 --> 00:49:19,520 Speaker 1: It's weird. It's true, it's weird, But you know, it's 857 00:49:19,560 --> 00:49:21,359 Speaker 1: always a reminder that we shouldn't try and do both 858 00:49:21,400 --> 00:49:24,239 Speaker 1: at the same time. But to bring it back to 859 00:49:24,400 --> 00:49:26,879 Speaker 1: Kola Shov, I do think this drives home a little 860 00:49:26,880 --> 00:49:30,920 Speaker 1: bit the susceptibility of ambiguous faces. You know that we 861 00:49:31,080 --> 00:49:34,480 Speaker 1: can if the face is ambiguous, we have to think 862 00:49:34,520 --> 00:49:37,880 Speaker 1: more about it, We have to think more about the context. 863 00:49:38,120 --> 00:49:42,280 Speaker 1: But you know, what is the relationship between um shot 864 00:49:42,360 --> 00:49:44,840 Speaker 1: A and shot B, right? I mean that would go 865 00:49:44,920 --> 00:49:47,799 Speaker 1: along with what mobs that all said in their background again, 866 00:49:47,840 --> 00:49:50,600 Speaker 1: which is that, you know, the broad finding of behavioral 867 00:49:50,680 --> 00:49:54,360 Speaker 1: research is that people rely most on context to interpret 868 00:49:54,400 --> 00:49:56,640 Speaker 1: the faces of others when the clarity of the facial 869 00:49:56,719 --> 00:49:59,880 Speaker 1: expression is low, So that could be ambiguity or other 870 00:50:00,080 --> 00:50:02,279 Speaker 1: things maybe or maybe just like it's hard to see, 871 00:50:02,880 --> 00:50:05,160 Speaker 1: and when the clarity of the context is high, so 872 00:50:05,239 --> 00:50:08,440 Speaker 1: when there's information in the context and less information in 873 00:50:08,520 --> 00:50:17,880 Speaker 1: the face, you reach for the context than well. Anyway, 874 00:50:17,920 --> 00:50:19,960 Speaker 1: I guess this all brings us back to one of 875 00:50:20,000 --> 00:50:24,239 Speaker 1: the questions posed by the Prince in Hensley paper, which is, 876 00:50:24,520 --> 00:50:28,520 Speaker 1: you know, I wonder if certain actors are just more 877 00:50:28,760 --> 00:50:32,560 Speaker 1: likely to um, more likely to give rise to this 878 00:50:32,680 --> 00:50:36,440 Speaker 1: effect than others are, and that again drawing on that 879 00:50:36,560 --> 00:50:39,680 Speaker 1: observation that there's actually a difference between a neutral face 880 00:50:39,719 --> 00:50:42,520 Speaker 1: and an ambiguous face. I was trying to think of 881 00:50:43,239 --> 00:50:48,440 Speaker 1: examples of actors who's what you might call blank or 882 00:50:48,560 --> 00:50:53,920 Speaker 1: neutral faces might tend more toward expressive ambiguity rather than 883 00:50:53,960 --> 00:50:57,720 Speaker 1: true neutrality. So even when their face is supposedly at rest, 884 00:50:57,960 --> 00:51:00,680 Speaker 1: you could look at it and and it would seem 885 00:51:00,800 --> 00:51:04,719 Speaker 1: valid to interpret a wide range of intense emotions to them. 886 00:51:05,120 --> 00:51:07,359 Speaker 1: The best example I could think of, and I didn't 887 00:51:07,400 --> 00:51:08,960 Speaker 1: pick him just because I love him as an actor, 888 00:51:09,000 --> 00:51:11,040 Speaker 1: though I do. The best example I could think of 889 00:51:11,239 --> 00:51:14,680 Speaker 1: was Toshiro Mfune, who you might know from a Cia 890 00:51:14,719 --> 00:51:16,640 Speaker 1: Kua Sawa movies. You know, he's the star of your 891 00:51:16,719 --> 00:51:20,080 Speaker 1: Jimbo and movies like that. I would say he is 892 00:51:20,200 --> 00:51:23,680 Speaker 1: somebody who, even when he's doing something very stoic with 893 00:51:23,840 --> 00:51:26,560 Speaker 1: his face, even when his face appears to be at rest, 894 00:51:27,239 --> 00:51:30,680 Speaker 1: you could easily imagine that it is expressing a range 895 00:51:30,760 --> 00:51:34,080 Speaker 1: of diametrically opposing emotions. And rob I I pasted in 896 00:51:34,160 --> 00:51:35,759 Speaker 1: a picture for you to look at. Here that's just 897 00:51:35,920 --> 00:51:38,600 Speaker 1: a portrait of him. I don't think this is even 898 00:51:38,680 --> 00:51:40,200 Speaker 1: from a film. I think this might just be like 899 00:51:40,280 --> 00:51:44,080 Speaker 1: a studio portrait. Still, because this is one where I've seen, 900 00:51:44,400 --> 00:51:46,800 Speaker 1: you know, like that he's done autographs on and stuff. 901 00:51:47,320 --> 00:51:50,440 Speaker 1: To my eye, in this portrait, he could be happy, 902 00:51:50,840 --> 00:51:54,000 Speaker 1: he could be sad, he could be affectionate, he could 903 00:51:54,120 --> 00:51:58,400 Speaker 1: be hungry, he could be angry. All seemed totally plausible 904 00:51:58,480 --> 00:52:01,440 Speaker 1: with the expression on his face. And I guess this 905 00:52:01,480 --> 00:52:03,839 Speaker 1: seems to correspond with the fact that I'd say he's 906 00:52:03,840 --> 00:52:08,880 Speaker 1: an actor known simultaneously for having a highly emotionally expressive 907 00:52:08,960 --> 00:52:14,399 Speaker 1: face and for often playing kind of stoic characters. Yeah. Yeah, 908 00:52:14,520 --> 00:52:17,279 Speaker 1: you think about the especially some of the samurai type 909 00:52:17,360 --> 00:52:19,640 Speaker 1: characters that he played, it attends to be an intense 910 00:52:19,920 --> 00:52:22,799 Speaker 1: stoicism to those characters. But at the same time, I mean, 911 00:52:23,280 --> 00:52:27,600 Speaker 1: you think of his the McBath character or the equivalent 912 00:52:27,640 --> 00:52:30,239 Speaker 1: of McBeth pretty wise and Throne of Blood. You know, 913 00:52:30,360 --> 00:52:33,000 Speaker 1: certainly he's you know, there's plenty of wide eyed crazy 914 00:52:33,080 --> 00:52:36,120 Speaker 1: shots in that film, especially towards the end. But yeah, 915 00:52:36,120 --> 00:52:37,560 Speaker 1: a lot of a lot of the characters he plays 916 00:52:38,200 --> 00:52:42,840 Speaker 1: have a certain sternness, a certain stoic quality, uh that 917 00:52:43,080 --> 00:52:47,160 Speaker 1: that has ultimately has an intense ambiguity to it. And 918 00:52:47,400 --> 00:52:50,160 Speaker 1: it makes me think about a difference that you know, 919 00:52:50,280 --> 00:52:53,800 Speaker 1: sometimes you read psychological studies that are measuring emotions in 920 00:52:53,960 --> 00:52:58,399 Speaker 1: some context, and they measure emotions in terms of both 921 00:52:58,760 --> 00:53:03,440 Speaker 1: valence and in tensity, where valence means what the emotion is, 922 00:53:03,640 --> 00:53:06,080 Speaker 1: so it could be like positive emotion or negative emotion, 923 00:53:06,680 --> 00:53:11,359 Speaker 1: and intensity is how strongly it is felt. Thinking about 924 00:53:11,400 --> 00:53:13,840 Speaker 1: this makes me wonder if maybe there are some people 925 00:53:14,000 --> 00:53:19,600 Speaker 1: whose emotional expression naturally tends to be high in intensity 926 00:53:20,080 --> 00:53:23,560 Speaker 1: even when the valence is unknown or unclear, If that 927 00:53:23,640 --> 00:53:27,279 Speaker 1: makes any sense. Yeah, yeah, so I wonder if that's 928 00:53:27,360 --> 00:53:30,480 Speaker 1: especially the kind of person that you use a picture of, 929 00:53:30,680 --> 00:53:33,719 Speaker 1: that kind of actor trying to do a neutral face. 930 00:53:33,880 --> 00:53:36,960 Speaker 1: But then you do a Coolishov type experiment and people 931 00:53:37,000 --> 00:53:39,520 Speaker 1: would be like, yes, you know, you show them looking 932 00:53:39,560 --> 00:53:41,879 Speaker 1: at the coffin, they're very sad. You show them looking 933 00:53:41,920 --> 00:53:44,839 Speaker 1: at the soup, they are ravenous. Whereas there are other 934 00:53:45,000 --> 00:53:49,560 Speaker 1: actors who whose face is just more successfully convey a 935 00:53:49,680 --> 00:53:52,279 Speaker 1: blank neutrality where people see it and they say, I 936 00:53:52,520 --> 00:53:56,560 Speaker 1: don't think this person is feeling anything. Yeah, yeah, I 937 00:53:56,640 --> 00:53:58,520 Speaker 1: think it's a good point, and to try and sort 938 00:53:58,520 --> 00:54:00,760 Speaker 1: of prove it out for our own purposes. You posted 939 00:54:00,880 --> 00:54:03,840 Speaker 1: this picture of a man in in our notes, and 940 00:54:03,880 --> 00:54:06,920 Speaker 1: I posted a picture of soup next to him. And indeed, 941 00:54:06,960 --> 00:54:08,279 Speaker 1: if I look at the two and I sort of 942 00:54:08,360 --> 00:54:10,320 Speaker 1: go back and forth, it's yeah, I can read. I 943 00:54:10,360 --> 00:54:13,920 Speaker 1: can lean into different interpretations like is he he is 944 00:54:14,000 --> 00:54:16,080 Speaker 1: angry that the soup has been served, maybe it was 945 00:54:16,160 --> 00:54:18,720 Speaker 1: served too early, or it's you know, it's clearly cold, 946 00:54:19,000 --> 00:54:21,200 Speaker 1: or he just had the soup yesterday and therefore he 947 00:54:21,239 --> 00:54:23,799 Speaker 1: has uh he has I rate. But he also could 948 00:54:23,800 --> 00:54:26,480 Speaker 1: be like, yes, now it it's time to to really 949 00:54:26,600 --> 00:54:31,879 Speaker 1: get into this soup. Yeah, or or various other interpretations. 950 00:54:32,160 --> 00:54:34,080 Speaker 1: You know. Weirdly, some of the other actors I know 951 00:54:34,160 --> 00:54:37,840 Speaker 1: who fit into this mold are not just film actors. 952 00:54:37,920 --> 00:54:39,640 Speaker 1: I mean a lot of them are film actors, but 953 00:54:39,800 --> 00:54:44,320 Speaker 1: especially people who have done like modeling, like fashion modeling 954 00:54:44,480 --> 00:54:47,960 Speaker 1: or art modeling, like Grace Jones comes to mind. Does 955 00:54:48,040 --> 00:54:51,320 Speaker 1: somebody who could have have a facial expression that is 956 00:54:51,440 --> 00:54:57,439 Speaker 1: ambiguous in valence but high in intensity. No, yeah, I definitely, yeah, 957 00:54:57,520 --> 00:55:00,640 Speaker 1: I definitely can see that with Grace Jones. I was thinking, 958 00:55:00,800 --> 00:55:02,360 Speaker 1: I was trying to think of good examples of this, 959 00:55:02,960 --> 00:55:06,120 Speaker 1: and uh like, my mind turned to some actors who certainly, 960 00:55:06,320 --> 00:55:09,160 Speaker 1: you know, have kind of like a smoldering uh stare 961 00:55:09,640 --> 00:55:11,319 Speaker 1: or have you know, the good at the stoic type 962 00:55:11,400 --> 00:55:14,040 Speaker 1: characters are, especially the sort of Joe cool characters, you know, 963 00:55:14,280 --> 00:55:16,279 Speaker 1: as I think of them, where you know, it's like 964 00:55:16,680 --> 00:55:20,080 Speaker 1: it's playing some cool, cool dude is like a detective 965 00:55:20,200 --> 00:55:22,640 Speaker 1: or something, and he's you know, he's acting pretty much 966 00:55:23,000 --> 00:55:26,080 Speaker 1: unfazed by everything around him. But I think the better 967 00:55:26,160 --> 00:55:30,080 Speaker 1: example I ended up turning to is Harry Dean Stanton, 968 00:55:30,600 --> 00:55:33,520 Speaker 1: who often played very you know, very sort of emotionally 969 00:55:33,640 --> 00:55:37,240 Speaker 1: muted characters. I would say, though not Joe cool characters, 970 00:55:37,320 --> 00:55:39,440 Speaker 1: you know, not not a character that's so far above 971 00:55:39,480 --> 00:55:42,239 Speaker 1: it all that he feels completely at ease. Oh, I 972 00:55:42,280 --> 00:55:46,080 Speaker 1: think Harry Dean's potentially another great example. Yeah. Yeah. And 973 00:55:46,600 --> 00:55:50,440 Speaker 1: another like actually kind of like a suite of answers 974 00:55:50,520 --> 00:55:54,040 Speaker 1: that came to mind were from the uh, the the 975 00:55:54,160 --> 00:55:57,680 Speaker 1: alien film franchise. The various actors that you had playing 976 00:55:57,880 --> 00:56:05,080 Speaker 1: androids um, specifically thinking of Ian Holme, Um, Lance Hendrickson, 977 00:56:05,200 --> 00:56:11,239 Speaker 1: and Michael Fassbender, all three very talented actors, um but um, 978 00:56:11,719 --> 00:56:14,960 Speaker 1: but in all cases they're supposed to be playing the 979 00:56:15,200 --> 00:56:19,400 Speaker 1: this artificial human type of being that has no emotions 980 00:56:20,120 --> 00:56:23,920 Speaker 1: but but has an intent and in depending on which 981 00:56:23,960 --> 00:56:26,960 Speaker 1: film you're landing on in which particular incarnation of the 982 00:56:27,040 --> 00:56:32,359 Speaker 1: android that intent maybe um benevolent or or might lean 983 00:56:32,440 --> 00:56:37,160 Speaker 1: more neutral or might be malicious um and interesting. Yeah, 984 00:56:37,680 --> 00:56:39,960 Speaker 1: I don't know if i'd go there with Ian Holme actually, 985 00:56:40,000 --> 00:56:44,440 Speaker 1: because Ian Holmes seems unusually capable of projecting absolute blank 986 00:56:44,560 --> 00:56:48,440 Speaker 1: neutrality where you don't get that that ambiguity that spins 987 00:56:48,480 --> 00:56:50,800 Speaker 1: off in all the directions. Like I think he would be. 988 00:56:51,000 --> 00:56:53,880 Speaker 1: He would be great to have people like absolutely fail 989 00:56:54,120 --> 00:56:57,759 Speaker 1: to reproduce the coolis shot results have him doing blank face, 990 00:56:58,160 --> 00:57:01,480 Speaker 1: but other ones you're saying, I agree, Yeah, so I don't. 991 00:57:01,520 --> 00:57:03,600 Speaker 1: I don't know. Like I was just thinking back on 992 00:57:03,680 --> 00:57:06,480 Speaker 1: those films, and even though these are the characters that 993 00:57:06,680 --> 00:57:10,520 Speaker 1: are not supposed to have emotional states, in some cases, 994 00:57:10,560 --> 00:57:12,520 Speaker 1: I feel like I have a better handle on their 995 00:57:12,560 --> 00:57:16,800 Speaker 1: emotional states versus other human characters in those pictures. Yeah, 996 00:57:17,200 --> 00:57:19,560 Speaker 1: but I have to admit I did not paste all 997 00:57:19,600 --> 00:57:22,560 Speaker 1: of their photos into our document and put them opposite soup, 998 00:57:22,640 --> 00:57:24,800 Speaker 1: so I haven't tested in myself. Oh you did put 999 00:57:24,920 --> 00:57:27,000 Speaker 1: fast Spender next to soup though, And I gotta say 1000 00:57:27,040 --> 00:57:30,320 Speaker 1: he looks hungry. Yeah, yeah, yeah, he looks. He does 1001 00:57:30,440 --> 00:57:32,920 Speaker 1: look like he is Uh, he's about to dine on 1002 00:57:33,000 --> 00:57:35,800 Speaker 1: some soup. Can't you just imagine a scene of him 1003 00:57:35,880 --> 00:57:41,120 Speaker 1: sensually teaching his twin how to peel a butternut squash? Yeah, 1004 00:57:41,160 --> 00:57:45,120 Speaker 1: that would be good, feeding each other's soup with wooden spoons. Yeah. Well, anyway, 1005 00:57:45,200 --> 00:57:47,760 Speaker 1: all this is just to say, and to be fair, 1006 00:57:47,840 --> 00:57:51,160 Speaker 1: maybe some studies have done this and I didn't realize it, 1007 00:57:51,240 --> 00:57:53,880 Speaker 1: but it seems like maybe one good move to try 1008 00:57:53,920 --> 00:57:59,240 Speaker 1: to avoid the the the the interactor effects of the 1009 00:57:59,520 --> 00:58:01,959 Speaker 1: of the STI mulus you use in cooler Shov type 1010 00:58:01,960 --> 00:58:05,280 Speaker 1: experiments is to just like get a whole lot of 1011 00:58:05,560 --> 00:58:09,320 Speaker 1: pictures of neutral faces and then serve them up at random, 1012 00:58:09,480 --> 00:58:11,680 Speaker 1: and so you can get kind of the neutral face 1013 00:58:11,800 --> 00:58:15,760 Speaker 1: photo averaged out over a big population, instead of having 1014 00:58:15,840 --> 00:58:20,080 Speaker 1: it fluctuate based on like how truly neutral your supposedly 1015 00:58:20,160 --> 00:58:24,240 Speaker 1: neutral face looks. I'd be delighted to hear from listeners 1016 00:58:24,320 --> 00:58:27,240 Speaker 1: out there what their thoughts are and their specific examples 1017 00:58:28,080 --> 00:58:32,760 Speaker 1: from cinema and from you know, the faces of various actors. 1018 00:58:33,160 --> 00:58:34,720 Speaker 1: You know, I wanted to come back to something that 1019 00:58:34,800 --> 00:58:37,280 Speaker 1: which which I thought is kind of interesting about this. Uh, 1020 00:58:37,680 --> 00:58:40,040 Speaker 1: even if you only accept that the cooler shov effect 1021 00:58:40,720 --> 00:58:45,400 Speaker 1: is rather modest or only applies sometimes, it is still 1022 00:58:45,480 --> 00:58:50,160 Speaker 1: pretty interesting that it indicates how flexible the human brain 1023 00:58:50,400 --> 00:58:56,240 Speaker 1: is at constructing artificial scenarios and still applying like human 1024 00:58:56,320 --> 00:58:59,720 Speaker 1: logic to them. That like, you know, you're not observing 1025 00:58:59,760 --> 00:59:02,280 Speaker 1: a real scenario in life where you're trying to guess 1026 00:59:02,320 --> 00:59:05,080 Speaker 1: if somebody is hungry. You're looking at a photo or 1027 00:59:05,080 --> 00:59:07,960 Speaker 1: you're looking at an image on a on a screen, 1028 00:59:08,360 --> 00:59:10,280 Speaker 1: and then it's being intercut with a you know, a 1029 00:59:10,400 --> 00:59:12,680 Speaker 1: coffin that they might be sad at, or just a 1030 00:59:12,800 --> 00:59:16,320 Speaker 1: picture of soup or something, and we we start applying 1031 00:59:16,480 --> 00:59:19,000 Speaker 1: the same logic we apply to real life to these 1032 00:59:19,080 --> 00:59:23,520 Speaker 1: obviously artificial stimuli. Yeah. Yeah, And I think it's a 1033 00:59:23,560 --> 00:59:27,320 Speaker 1: great reminder of just how film works, and and and 1034 00:59:27,440 --> 00:59:30,320 Speaker 1: other mediums of ore, but especially film, how you know 1035 00:59:30,960 --> 00:59:33,800 Speaker 1: there they still require a viewer. And if there's not 1036 00:59:33,880 --> 00:59:38,040 Speaker 1: a viewer, uh, there's there's not a movie goer, there's 1037 00:59:38,080 --> 00:59:40,920 Speaker 1: no film experience since therefore there's no film, and so 1038 00:59:41,080 --> 00:59:43,760 Speaker 1: there's no matter how polished the thing on the screen is, 1039 00:59:44,360 --> 00:59:48,360 Speaker 1: there's something that takes place not only between the film 1040 00:59:48,520 --> 00:59:51,600 Speaker 1: and the viewer, but inside the viewer's mind. That's that's critical, 1041 00:59:51,960 --> 00:59:53,640 Speaker 1: and that a lot of times we don't notice how 1042 00:59:53,720 --> 00:59:56,840 Speaker 1: many gaps were filling in as film viewers, like, Yeah, 1043 00:59:56,920 --> 00:59:59,920 Speaker 1: you don't realize how much work you're doing, and it's 1044 01:00:00,040 --> 01:00:02,560 Speaker 1: work that is apparently pretty easy to do. It's just 1045 01:00:02,720 --> 01:00:05,919 Speaker 1: something we we tend to do pretty much automatically while 1046 01:00:05,960 --> 01:00:09,200 Speaker 1: we're watching movies is fill in those gaps of logic, 1047 01:00:09,440 --> 01:00:13,640 Speaker 1: make connections between one image and another, make assumptions about 1048 01:00:13,720 --> 01:00:16,120 Speaker 1: what's going on in an actor's head when they're portrayed 1049 01:00:16,160 --> 01:00:19,400 Speaker 1: on screen based on the context or the music, you know, 1050 01:00:19,520 --> 01:00:22,840 Speaker 1: what was shown just before after. But it's one of 1051 01:00:22,840 --> 01:00:24,840 Speaker 1: those things where it gets pretty weird when you start 1052 01:00:24,920 --> 01:00:27,760 Speaker 1: to notice all of those like assumptions you're having to 1053 01:00:27,840 --> 01:00:30,320 Speaker 1: make and mental work you're having to do for a 1054 01:00:30,440 --> 01:00:33,000 Speaker 1: movie to make sense, which in reality is a flickering 1055 01:00:33,080 --> 01:00:36,840 Speaker 1: succession of of moving images, which you know, sometimes if 1056 01:00:36,880 --> 01:00:39,360 Speaker 1: you were to be very literal about them, are are 1057 01:00:39,480 --> 01:00:42,240 Speaker 1: totally unconnected. Like you see like a staircase that's from 1058 01:00:42,280 --> 01:00:44,720 Speaker 1: one state and then a house that's from another, and 1059 01:00:44,800 --> 01:00:47,240 Speaker 1: then somebody's coming in through a front door, and you 1060 01:00:47,360 --> 01:00:49,160 Speaker 1: just connected all you know, this is all in the 1061 01:00:49,240 --> 01:00:53,320 Speaker 1: same place. Persons just moving through their their daily routine. Yeah, 1062 01:00:53,920 --> 01:00:57,480 Speaker 1: we often think of viewing films and watching TV programs 1063 01:00:57,520 --> 01:00:59,400 Speaker 1: as being kind of a shut your brain off kind 1064 01:00:59,440 --> 01:01:01,520 Speaker 1: of a situation, and at least with certain types of 1065 01:01:02,360 --> 01:01:05,200 Speaker 1: of film and TV. And you know, we think that, Okay, 1066 01:01:05,480 --> 01:01:07,520 Speaker 1: if it's a it's a highly crafted product, we're not 1067 01:01:07,520 --> 01:01:10,040 Speaker 1: gonna have to mainstream product, we're not gonna have to 1068 01:01:10,120 --> 01:01:12,800 Speaker 1: do much thinking. It's gonna hold our hand the whole way. 1069 01:01:12,920 --> 01:01:15,440 Speaker 1: But but yeah, even even in the case if you're 1070 01:01:15,440 --> 01:01:19,320 Speaker 1: sort of um, you know, by the numbers summer blockbuster, uh, 1071 01:01:19,440 --> 01:01:22,480 Speaker 1: you know, very much repeating a plot you've seen before, 1072 01:01:22,640 --> 01:01:25,160 Speaker 1: with the sort of characters you've seen before, your brain 1073 01:01:25,280 --> 01:01:27,840 Speaker 1: is still filling in these little gaps, like you say. 1074 01:01:28,200 --> 01:01:30,520 Speaker 1: But on the same hand, I think one one thing 1075 01:01:30,600 --> 01:01:32,400 Speaker 1: we can drive home based on what we've been discussing 1076 01:01:32,480 --> 01:01:35,320 Speaker 1: here is that that the opposite uh in a way 1077 01:01:35,440 --> 01:01:37,600 Speaker 1: is true. Is that if you're dealing with a film 1078 01:01:37,680 --> 01:01:40,200 Speaker 1: that's say, is uh, you know of a of a 1079 01:01:40,320 --> 01:01:42,560 Speaker 1: genre you're not that familiar with, or a time period 1080 01:01:42,640 --> 01:01:46,560 Speaker 1: of of filmmaking and not that familiar with. Um, perhaps 1081 01:01:46,640 --> 01:01:48,920 Speaker 1: it's a you know, more more of an art film 1082 01:01:49,000 --> 01:01:51,600 Speaker 1: where it's you know, foreign language, etcetera. A lot of 1083 01:01:51,680 --> 01:01:55,240 Speaker 1: it is still going to come down to human or 1084 01:01:55,360 --> 01:01:59,600 Speaker 1: humanoid entities interacting with things in each other, and then 1085 01:01:59,640 --> 01:02:03,280 Speaker 1: our ain is going to make presumptions about their mental 1086 01:02:03,360 --> 01:02:06,440 Speaker 1: state and their emotional state. Oh yeah, yeah, you you 1087 01:02:06,600 --> 01:02:09,640 Speaker 1: infer drama even when the thing you're looking at is 1088 01:02:09,680 --> 01:02:13,240 Speaker 1: almost actively resisting it, and that that goes beyond movies. 1089 01:02:13,320 --> 01:02:16,880 Speaker 1: In fact, I mean what is drama. Drama is somebody 1090 01:02:17,000 --> 01:02:19,520 Speaker 1: wanting something or trying to get something and then coming 1091 01:02:19,600 --> 01:02:23,640 Speaker 1: up against resistance in some way. Uh. People infer those 1092 01:02:23,720 --> 01:02:27,000 Speaker 1: kinds of dramas on like balls rolling around on the table. 1093 01:02:27,760 --> 01:02:30,200 Speaker 1: They're literally studies of that. You know, people will say, 1094 01:02:30,240 --> 01:02:33,640 Speaker 1: like the ball wanted to go down in this hole, 1095 01:02:33,800 --> 01:02:36,080 Speaker 1: but it you know, it couldn't get there because something 1096 01:02:36,240 --> 01:02:39,680 Speaker 1: was preventing it. All right, we're gonna go ahead and 1097 01:02:39,680 --> 01:02:41,240 Speaker 1: close it out there, but we would love to hear 1098 01:02:41,320 --> 01:02:43,640 Speaker 1: from everybody if you have particular thoughts on the clue 1099 01:02:43,640 --> 01:02:49,040 Speaker 1: Shov effect. Various examples and studies we've discussed in these episodes. Uh, 1100 01:02:49,160 --> 01:02:53,960 Speaker 1: some of the various examples from from film and acting 1101 01:02:54,080 --> 01:02:56,640 Speaker 1: that we have alluded to, Perhaps you have some better 1102 01:02:56,720 --> 01:03:00,240 Speaker 1: examples that you would like to bring to our mention, 1103 01:03:00,560 --> 01:03:03,200 Speaker 1: just right in and let us know. In the meantime, 1104 01:03:03,200 --> 01:03:04,920 Speaker 1: if you would like to check out other episodes of 1105 01:03:04,960 --> 01:03:07,160 Speaker 1: Stuff to Blow Your Mind, check it out in the 1106 01:03:07,200 --> 01:03:09,640 Speaker 1: Stuff to Blow Your Mind podcast feed. You'll find that 1107 01:03:09,720 --> 01:03:12,280 Speaker 1: wherever you get your podcasts. We have core episodes on 1108 01:03:12,400 --> 01:03:16,320 Speaker 1: Tuesday and Thursday. We have a listener mail on Monday, 1109 01:03:16,680 --> 01:03:19,680 Speaker 1: short form artifact episode on Wednesday, and on Friday we 1110 01:03:19,760 --> 01:03:21,960 Speaker 1: do Weird how Cinema. That's our time to set aside 1111 01:03:22,080 --> 01:03:26,640 Speaker 1: most serious matters and just discuss a weird film. Um. 1112 01:03:27,000 --> 01:03:28,640 Speaker 1: If you want a quick way to get to our podcast, 1113 01:03:28,680 --> 01:03:30,080 Speaker 1: you can just go to stuff to Blow your Mind 1114 01:03:30,120 --> 01:03:32,320 Speaker 1: dot com. That should still redirect you over to the 1115 01:03:32,480 --> 01:03:36,240 Speaker 1: I heart listing for our page. Huge thanks as always 1116 01:03:36,320 --> 01:03:39,760 Speaker 1: to our excellent audio producer Seth Nicholas Johnson. 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