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06 OCTOBER 2012

A social mirror to the prevalence of casual homophobia on Twitter

"This website is designed as a social mirror to show the prevalence of casual homophobia in our society. Words and phrases like 'faggot,' 'dyke,' 'no homo,' and 'so gay' are used casually in everyday language, despite promoting the continued alienation, isolation and - in some tragic cases - suicide of sexual and gender minority (LGBTQ) youth.

We no longer tolerate racist language, we're getting better at dealing with sexist language, but sadly we're still not actively addressing homophobic and transphobic language in our society.

Let's put an end to casual homophobia. Speak out when you see or hear homophobic or transphobic language from friends, at school,

in the locker room, at work or online. Use #NoHomophobes to show your support. And visit one of our resource websites to get more involved."

(NoHomophobes.com)

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TAGS

#NoHomophobes • alienation • casual expression • casual homophobia • casual reference • critiquecultural signalsdata analysisdykeeveryday • everyday language • faggot • gay • gender minority • homo • homophobia • homophobic language • information designintoleranceisolation • LGBTQ • locker room • metrics • minority • mirror • no homo • NoHomophobes • racist language • representation • sexist language • sexual minority • so gay • social activismsocial changesocial commentsocial differentiation • social mirror • social normssocial responsibilitysuicide • transphobic • transphobic language • TwitterTwitter streamwords and phrasesyouth

CONTRIBUTOR

Simon Perkins
26 SEPTEMBER 2012

In reply to Barry Salt on attention and the evolution of Hollywood film

"In our recent paper (Cutting, DeLong, & Nothelfer, 'Attention and the evolution of Hollywood film', Psychological Science, 2010, 21, 440-447; henceforth AEHF), we were interested in the shot structure in a reasonable sample of films across 70 years and in how that structure has changed. Our main conclusion was that the pattern of shots in more contemporary movies has come to match better the large-scale structure of human attention. In particular, a cut between shots forces the reallocation of attentional resources to the new scene or to the new vantage point, and the pattern of the length of those shots reflects natural tendencies of how attention ebbs and flows over as much as an hour and more. The structure of both attention and, more and more often, contemporary film appears to follow a 1/f pattern, sometimes called pink noise.

The 1/f pattern can be thought of as a simultaneous combination of many transverse, nonsynchronous waves whose up and down-ness, or amplitude (power is proportional to the square of the amplitude), is fixed by their wavelength (or the reciprocal of frequency, hence 1/f). Thus, the big (up and down) waves are also long waves (in time); smaller waves are shorter waves and proportionately so. For example, a relatively big wave might be exemplified by 60 consecutive shots that are relatively long followed by 60 shots that are relatively short, and with that pattern repeating; shorter and longer waves would also occur overlapping and within this original wave.

Blogged science reporting vs. science

Popular representations of science often skew things, and occasionally they simply get things wrong. Indeed, there were a number of howlers that appeared in the blogosphere about our research. As evidence, all one need do is to check out the title of the first popular piece on our work (http://www.newscientist.com/article/mg20527483.900-solved-the-mathematics-of-the-hollywood-blockbuster.html). Fortunately, the article’s content was more reasonable and more accurately reflected what we found.

Now Barry Salt has joined the mix, and we are quite happy with his comment on AEHF. Among all possible responses, one can ask for nothing better than to be 'usefully provocative.' Against the misrepresentation by others, Salt (http://www.cinemetrics.lv/salt_on_cutting.php) rightly notes that we did not try to account for the box office success of movies. We didn’t even focus on the highest grossing movies, or attempt to use low grossing movies as a control group. Nor did we try to discern what makes a good film. In fact, we specifically reported that our results did not correlate with IMDb ratings of films in our sample. Salt also noted that our cut-finding process was more time consuming than perhaps necessary. Wary of errors often made in typical cinemetric-style cut finding (see Smith & Henderson, 2008, 'Edit blindness,' Journal of Eye Movement Research, 2, 1-17), we deliberately sacrificed efficiency for accuracy, with multiple checks (digital and ocular) throughout the process. But in trying to account for our results Salt also raises two other issues to which we thought it important to respond. He calls them basic (about scene structure) and historical (concerning changes in ASL and shot length distributions). Let me consider them in reverse order.

Historical near parallels: Changes in ASL and in power spectra

Clearly, shot lengths have become shorter over the course of the 20th century and into the 21st. Salt updates his past data with an elegant graph in his commentary. In AEHF, we found that, since about 1950 or so, films have increasingly adopted a shot structure that approaches a 1/f pattern (pink noise). One might think these two are related – and indeed they are correlated. But there is no causal link between them.

Salt (Moving into Pictures, 2006) was first to note that the shot distributions of most films tend to follow a lognormal distribution and generalizing this he produced two new graphs in his commentary, one for Catherine the Great (1934) and one for Derailed (2002). In showing these graphs Salt is concerned about is what psychologists call a floor effect. That is, the average duration of shots may have decreased to a point where they can decrease no further without failing to give the viewer sufficient time to perceive shot content. When plotting and analyzing shot duration data linearly, as Salt and many others have done, this seems like a genuine possibility. However, plotted logarithmically, no floor exists.

What lognormality means is that if one took the logarithm of every value in the distribution and then replotted the data, the distribution would look normal – like a bell-shaped curve, more or less. Shown below are the log-scaled distributions for four films from our sample, two from 1935 and two from 2005:

Chart

Despite 70 years, fairly dramatic differences in ASL, and the great differences in number of shots per film, all four distributions look generally the same. The important point is that log-scaled shot-length distributions for films look normal and that normal distributions have no real floor (the logarithm of zero is undefined). Likely, as shot lengths in films get shorter, shots measured in fractions of seconds (not just seconds) will continue to be lognormal.

Our analysis in AEHF started by normalizing the shot distribution of each film. That is, the mean is set to zero (subtracting the ASL from each shot length) and the standard deviation is set to one (dividing the value above by the standard deviation of the shots in the whole film). This creates what is called a unit normal distribution, and it is a standard statistical procedure when comparing the shapes of distributions. This procedure alone would likely nullify the differences shown by Salt for Catherine the Great and Derailed, and it was on such unit-normal data that we first ran our Fourier and power analyses. But just to be certain, in AEHF we also performed that same normalizing analysis after log scaling shot lengths for each film. Results were the same in either case.

Thus, diminished ASLs cannot cause our power spectra results; ASL is factored out before the analysis is done. Also, we found no evidence in the changes in film distributions in our film sample as ASL diminishes, and we also renormalized the distributions before our analysis. Moreover, as counterexamples, consider The 39 Steps (1935) with an ASL of 10.8 s and a slope of .93 (1.0 is the slope for a 1/f pattern) and GoldenEye (1995) with an ASL of 3.6 s and a slope of .96; or consider Annie Get Your Gun (1950) with an ASL of 14.9 s and a slope of 1.18 and the Revenge of the Sith (2005) with an ASL of 3.57 s and a slope of 1.14.

Nonetheless, Salt rightly notes our power spectra results are still correlated with ASLs for our sample of films. It is just that neither has caused the other. One should then ask: What has caused the change in power spectra over the last 50 years or so? Our guess in AEHF was that there has been a kind of cultural transmission among filmmakers about what seems to work in shot composition and that this was at the root of the process. In other words, the increasingly 1/f-like pattern emerged from what would be collectively regarded by filmmakers as good film construction, but without anyone needing to know what 1/f is or really means. Another possible cause, one we hadn’t considered, emerged in my correspondence with Hollywood film editors after AEHF appeared. Editors now have much more film footage to draw upon than they did 50 and more years ago. Thus, they have many more choices they can make in composing shots in and across scenes. It seems possible, then, that the ability to make better choices has also contributed to the development of a 1/f structure in contemporary film.

Also, in discussion of the differences between Catherine the Great and Derailed, Salt also reported the Lag-1 autocorrelations for the two films (about .12 and .20, respectively) and suggested these would make a difference, perhaps contributing to what we found in our power spectra. These lag correlations map the length relations between Shots 1 & 2, 2 & 3, 3 & 4, and so forth along the length of the film. This is a good beginning but Lag-1 data alone can be misleading. The Lag-1 correlations for Goodfellas (1990) and Those Magnificent Men and Their Flying Machines (1965) are .33 and .30, respectively; but their modified autoregression indices (mARs) as we calculated them (autoregression looks at part of the partial autocorrelation function, which we smoothed), using data from Lags 1 through Lags 20 (Shots 1 & 21, 2 & 22, 3 & 23, etc., out to the end of the film) are 2.13 and 4.0. This means that the statistically reliable, local correlational structure across shots in Goodfellas is only about half that of Flying Machines, although their Lag-1 data were about the same. More simply, significant shot-length relations extend to only about 2 shots across the former film (aggregated across Shots 1 to 3, 2 to 4, etc.), compared to 4 shots in the latter (aggregated across Shots 1 to 5, 2 to 6, etc.). The complete autocorrelation function (Lag 1 to Lag n, where n is as much as half the value of the number of shots in a film) gives the record of shot relations across a whole film. The power spectrum, which we calculated for all films to derive our 1/f approximations, is the Fourier twin of the complete autocorrelation function.

Basic film units: Shots, scenes, and beyond

In AEHF we looked at shot structure across films without regard to scene structure. In his essay 'Speeding up and slowing down' (http://www.cinemetrics.lv/salt_speeding_up_down.php), Salt performed a moving average analysis of ASLs in several films, particularly Ride Lonesome (1959). He found, not surprisingly, that different scenes in a given film have different ASLs. In a moving average window this creates a wavy pattern on a larger scale than that for shots. Salt also describes this in his comment on AEHF as a '’tension-release’ pattern' often found elsewhere, as in music. We wholeheartedly endorse this idea. More importantly, however, Salt’s moving average result exactly reflects part of what we found in the power spectra analyses.

That is, the Fourier and power analysis that we performed (doggedly and mechanically) looked for waves in the shot-length sequences of each film, where those waves could be of 2, 4, 8, 16, 32, 64, 128, 256, 512 shots long and sometimes longer. Notice that these numbers form a progression in powers of 2. They do so in order that the measured waves be completely independent. These waves are assessed within windows that move along the complete length of the shot vector (the list of consecutive shot lengths in a film). Thus, size-2 wave is fit serially to Shots 1-2, 2-3, 3-4, etc, out to the end of the film; the size-8 wave is fit serially to Shots 1 through 8, 2-9, 3-10, etc; and the size-512 wave is fit serially to Shots 1 through 512, 2-513, 3-514, etc. This can begin to look like a moving average analysis, which Salt endorses, but it is different. It looks at different independent window sizes and it does not average, but finds the best fitting sine wave within each moving window. Salt’s scene analysis of Ride Lonesome shows between about 5 and as much as 100 shots per scene, and with a moving average window he generates loopy waves that correspond to them. By our analysis, any wave with lengths in this range will contribute to the measured power in the size-4 through size-128 shot-length waves of the Fourier and power analysis. In particular, a 100-shot scene that contrasts with prior and subsequent scenes in ASL will contribute to both the size-64 and size-128 wave. In this way, the different-length scenes contribute power to the mid-range of the 1/f pattern.

What we think is more striking about our AEHF results, however, is that there are such waves in film that are considerably larger than mean scene length. That is, for a 1/f pattern to emerge, there have to be waves of similar-length shots coursing through an entire film that are in the range of 256, 512, out to even 1024 shots apart. In contemporary films this can be in a range from 10 to as much as 60 minutes. This places these waves well beyond scene length and roughly puts them at the scale of film acts, endorsed in different ways by Syd Field (1979, Screenplay) and by Kristin Thompson (1999, Storytelling in the new Hollywood). Remember, we introduced our results above in terms of allocating attention to film over as much as an hour and more; this involves 'tension and release' at very different scales.

In addition, Salt and others have highlighted our result that action films tend to approach a 1/f structure more than the other genres we explored (adventure, animation, comedy, drama films). It is by no means the case, however, that action films always have close to a 1/f shot-length profile. We recently analyzed the James Bond film Quantum of Solace (2008). Despite its 1.71 ASL (trimming out the glossy credit sequence after the opening scenes), it doesn’t approach a 1/f structure. It fails to produce this structure precisely because it has few long-range similarities in shot-length patterns across the range of 512 to 1024 shots.

In summary and in response to Salt, (1) our power analysis is causally unrelated to ASL even though the two have developed more or less in parallel over the last 50 years or so, (2) we find no evidence for the change in shot distributions in popular films in our sample across time; they are all lognormal to reasonable approximation, and (3) the ASL differences he found in scene-length structure are contained within the 1/f-like patterns that we found, but we also found evidence for longer act-length structure as well. So, do we want to talk about the structure of film units – shots, scenes, and acts – or do we want to talk about 1/f structure? I would hope that there is room to talk about, and to learn from, both. I think that we can all endorse the idea that cinemetrics can be done in many ways."

(James Cutting, Cinemetrics.lv)

TAGS

1/f law • AEHF • ASL • attentionattention span • attentional resources • average shot length • Barry Salt • blockbuster • blogged science • blogospherecinema • cinemetrics • consecutive shots • contemporary film • contemporary movies • cut finding • cut-finding process • cuts between shots • data abstraction • ebbs and flows • evolution of Hollywood film • film • film cuts • film ratings • film structure • floor effect • highest grossing movies • highest-grossing films • Hollywood • human attention • IMDb • James Cutting • linearly • lognormal distribution • low grossing movies • lowest-grossing films • metricsneurocinematics • nonsynchronous waves • pattern • pattern of shots • pink noise • popular representations • popular representations of science • psychological sciencescenescene compositionscene designscience • shot distributions • shot duration • shot length • shot structure • simultaneous combination • up-and-downness • vantage point • what makes a good film

CONTRIBUTOR

Tessa Szwarnowska
29 APRIL 2012

Citations and impact factors are old hat: the Web 2.0 generation needs metrics to match today's scholarship

"As a young academic, I am reliably informed that the landscape of scholarly communication is not what it was 20 years ago. But, despite all that has changed, it seems that we still largely rely upon the same tired and narrow measures of quality and academic impact - namely, citation counts and journal impact factors.

As someone who has used the internet in almost every aspect of their academic work to date, it's hard for me to ignore the fact that these mechanisms, in predating the web, largely ignore its effects.

By holding up these measures as incentives, we appear to have our eye firmly fixed on the hammer and not the nail, adjusting our research habits in order to maximise scores and ignoring issues such as why we publish in the first place."

(Matthew Gamble, 28 July 2011, Times Higher Education)

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TAGS

academic blogs • academic discussion • academic impact • academic papers • academic work • alt-metrics • alt-metrics community • alt-metrics movement • altmetrics.org • assessing impact • assessment of scholarship • blogCERNcitation • citation counts • citation-based measures • citation-based measures of impact • diverse metrics • engaged scholars • existing measures • funding decisions • Harvard Universityimpact • impressions of impact • incentive • Internet • journal impact • journal impact factors • journal output • measurementmeasurement of impactMendeleymetrics • narrow measures • narrow measures of academic impact • narrow measures of quality • new measurement frontier • online • online reference-management service • peer review • platform for scholarly communication • practices of scholarly communication • products of scholarly communication • publication of academic papers • quantitative study of scholarship • ReaderMeter • readermeter.org • real-time readership • reference manager • research habits • research impactresearch output • Rouse Ball • Samuel Arbesman • scholarly activity • scholarly activity on the web • scholarly communication • scientific discoveries • second scientific revolution • Tim Berners-Lee • timely indications of impact • Timothy Gowers • traces of scholarship • TwitterUniversity of CambridgeUniversity of North Carolina • utility of the web • Web 2.0 • web as a platform • young academics

CONTRIBUTOR

Simon Perkins
19 SEPTEMBER 2011

Unistats: UK university comparison site

"Unistats lets you search, review and compare official information about universities and colleges in the UK, and the subjects they offer. It includes results from the National Student Survey – where more than 220,000 students give their views about the quality of their higher education experience. ...

HEFCE (the Higher Education Funding Council for England)¹ owns the Unistats websites and has contracted UCAS to manage the delivery and maintenance of these websites on its behalf."

(Unistats, UK)

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TAGS

accountability • admissions service • best practicecolleges • comparison site • conservatoire • Conservatoires UK Admissions Service • DEL • Department for Employment and Learningeducationeducation sectorgood practiceGraduate Teacher Training RegistryHEFCEHEFCW • high quality • higher educationHigher Education Funding Council for EnglandHigher Education Funding Council for Walesinformationknowledge territorialisationlegitimate scholarly practices • localised learning requirements • metricsNational Student Survey • Northern Ireland and the Scottish Funding Council • NSS • postgraduate certificate • practice-basedpublic money • quality of experience • research metrics • reviews • SFC • student viewsstudentsUCASUKUK Postgraduate Application and Statistical ServiceUKPASSundergraduate • Unistats • universitiesuniversity admissionswebsite

CONTRIBUTOR

Simon Perkins
20 MAY 2010

Research: a process of investigation leading to new insights effectively shared...

"The proposals for a new approach to the assessment and funding of research - set out last year in the Higher Education Funding Council for England's consultation paper on the research excellence framework - have sparked more than a few rows.

Much of the conflict has revolved around whether or not the economic and social impact of research should feature in the regime that will replace the research assessment exercise. ...

Our starting point should be to remember that the RAE was deeply flawed. It was dominated by vested interests, was embarrassingly subjective and seriously undervalued those scholars who bridge the worlds of academe and practice.

The REF is, then, a major step forward from the RAE not least because it broadens the definition of research. To suggest, as the REF does, that research is 'a process of investigation leading to new insights effectively shared' invites all scholars to think afresh about how they communicate their research findings and to whom. ...

Yes, there are challenges in research impact assessment. New thinking, around, say, research 'possibilities' is needed. But once academics recognise that research findings should be 'shared', we have made a significant step forward. By definition we are now discussing research impact or, at least, potential research impact.

However, the intellectual argument relating to research impact, rather like the debate about the expansion of university public engagement activities, goes much deeper than a discussion of how scholars can improve the manner in which they communicate with different audiences - important as this is.

Rather it concerns a reshaping, for some disciplines at least, of the way scholarship is conceived. It heralds a move towards the notion of 'engaged scholarship'. Many UK academics - medics are a classic example - are already actively engaged with stakeholders outside the campus in the process of defining research questions and co-producing new knowledge.

This is not to suggest that all scholars should be 'engaged scholars' - indeed, that would be a bad thing. But the research impact debate can open up the possibility of broadening the definition of scholarship."

(Robin Hambleton, 4 February 2010, Times Higher Education)

TAGS

2010 • a process of investigation leading to new insights effectively shared • assessing impact • definition • discoveryengaged scholarsengagementenquiryfindingsHEHEFCEHigher Education Funding Council for Englandimpactmeasurement of impactmetricspublishingRAEREFresearchResearch Excellence Frameworkresearch fundingresearch outputscholarshipsharingUK

CONTRIBUTOR

Simon Perkins
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