Sunday, December 2, 2012

Never Let Significance Get in the Way of a Good Story???

Via Seamus Ross, great example of misrepresenting research and the statistical significance debate, in this article by Robin McKie for The Guardian. Here's a short excerpt:

They are mainstay stories of tabloid newspapers and women's magazines, linking common foods from burnt toast to low-fat salad dressing to cancer. But now US scientists have warned that many reports connecting familiar ingredients with increased cancer risk have little statistical significance and should be treated with caution. 
"When we examined the reports, we found many had borderline or no statistical significance," said Dr Jonathan Schoenfeld of the Harvard School of Public Health in Boston. 
In a paper in the American Journal of Clinical Nutrition, Schoenfeld and his co-author, John Ioannidis of Stanford University, say trials have repeatedly failed to find effects for observational studies which had initially linked various foods to cancer. Nevertheless these initial studies have often triggered public debates "rife with emotional and sensational rhetoric that can subject the general public to increased anxiety and contradictory advice".

Thursday, November 22, 2012

Class Mini Ethnography Assignment

Here are the descriptions/options Harrison gave in class this week. Hope you had fun! OPTION 1 - MINI-ONLINE RESEARCH ASSIGNMENT You are an aspiring research assistant for a major social science project entitled “Emotional Information Seeking: ICTs and the commercialization of emotional and affective spaces online.” The project broadly investigates why ICTs are increasingly tailored towards emotional communication, resources, and identities, as part of a larger trend in marketing and commercialization. At this stage it is too early to undertake in-depth qualitative interviews. Your supervisor has asked that you select a specific example of an online environment tailored towards emotional information seeking, which might serve as an ideal case study for the project. Either individually or in small groups, pick any example, and prepare a 200 - 400 word explanation of the site/app. Include what it is, who it is tailor to, what emotional relations might exist, why it would make an ideal case study for the larger project, and (if applicable) the potential methodological challenges you will have to address. Post to blog. OPTION 2 - MINI-ETHNOGRAPHY OF INFRASTRUCTURE You are an aspiring research for a large social science project which broadly examines how urban infrastructure is being reconfigured by networked ICTs. As an exploratory study, your supervisor has asked that you go out “in the wild” and pick a particular infrastructure as a potential case study. She has no requirements or expectations concerning what kind of infrastructure you choose, and you have a carte blanche to interpret it however you see fit. Either individually, or in small groups, pick any example of something you consider to be infrastructure, and analyze it using Star’s (1999) analytical framework. Try and make the familiar strange. Prepare a 200-400 word write-up detailing your analysis. Post to blog.

Monday, November 5, 2012

Awesome new visual/content analysis research tool: ImagPlot

ImagePlot of Mondrian 
©2011 Manovich, UCSD, Software Studies

This free, data analysis/visualization tool, released a couple of years ago by Lev Manovich's Software Studies Initiative, appears to have some pretty AMAZING potential for facilitating large-scale media content/visual analysis. It allows you to view, sort through and analyze large image and media collections in a single visualization composed of the actual images in the data set. The visualization can be organized in a variety of ways (date, colours, etc.), which means you can also use it for identifying trends or patterns, make comparisons, discover outliers and clusters, track changes over time, etc. In relation to today's class, imagine doing an analysis of toy ads over the past 50 years, and tracking the emergence and spread of the predominance of pink/blue, as currently observed in JeongMee Yoon's photo project

According to the ImagePlot website, you can also use the tool to turn the visualizations into animations.

I've seen some of the results (e.g. the Freakangels webcomic archive visualizations are especially cool), and am really looking forward to finding out firsthand what this puppy can do (have been looking forward to this for awhile, but haven't had any appropriate content analysis projects come up of late). 

If any of you end up downloading it and testing it out, be sure to let me and the rest of the class know what you think! 

Here's an excerpt of the description posted on the ImagePlot Overview page:
"ImagePlot is a free software tool that visualizes collections of images and video of any size. It is implemented as a macro which works with the open source image processing program ImageJ. [...] Existing visualization tools show data as points, lines, and bars. ImagePlot's visualizations shows the actual images in your collection. The images can be scaled to any size and organized in any order - according to their dates, content, visual characteristics, etc. Because digital video is just a set of individual still images, you can also use ImagePlot to explore patterns in films, animations, video games, and any other moving image data."

Sunday, October 28, 2012

Monday, October 15, 2012

Wednesday, October 10, 2012

The Importance of Questioning Correlations

On the topic of correlations....this story came out a couple of weeks ago, about a recent study linking equal division of labour within couples to higher divorce rates. The most interesting thing about this is the way the study was reported in the media - with headlines like:

Significantly, rather than jump on the premature-conclusion-bandwagon, many other journalists questioned the study's conclusions, pointed out that correlation is not causation AND considered the very compelling possibility of a spurious relationship (in which "traditional values" becomes an overlooked, potentially confounding, variable). For example, as Wendy Leung wrote in the Globe & Mail:
According to the Telegraph, a new study out of Norway has found that divorce rates are as much as 50 per cent higher among couples that share the load equally, compared with households where women do the majority of the chores. But wait a minute. Aren’t households in which women do all the cooking and cleaning simply more traditional, and less inclined to see divorce as an option? The researchers acknowledge this could be one explanation.
FYI, a "confounding variable" is something that obscures the relationship between an independent and a dependent variable - in this case the relationship between "shared housework" and "divorce rates".  The argument Leung and others make is that "traditional values" may also be impacting upon both divorce rates AND housework distribution in significant ways that are overlooked in simplistic comparisons of housework and divorce. i.e. couples with more traditional values are less likely to get divorced AND less likely to share the housework equally. If a number of such couples were included in the study, how does this problematize the conclusion (or more accurately, the newspaper headlines) that sharing housework "leads" to divorce?

The sloppiness of the study (& its conclusions) itself has been noted by several journalists, but this article by Jen Doll in The Atlantic delves into things a bit more in depth, reviews some of the relevant academic literature (much of which deeply contradicts the idea that housework causes divorce), interviews with experts, etc. A really key point that Doll makes is that other than describing the country of origin, few if any of these news reports pinpoint the resesearchers' affiliation(s). This is a pretty crucial omission - is this a university study? A study conducted by a particular organization, charity, church, think tank, political party??? An informal survey some guy did of his friends and family???? Fascinating to see how studies like these end up as news headlines, while others (most) are ignored completely. For INF1240 it's also interesting to see how a deeper knowledge of research methods (incl. research design and data analysis) can be useful in questioning the research AND how it is portrayed in public/news discourses.

A Very Brief Intro to Correlations

Via Sociological Images, a great graph (any clear, easy to read graph is pretty great) and interesting analysis of the *positive correlation between income and SAT scores, from data published by The College Board. There's a pretty strong relationship implied here - one that raises questions about the ongoing reproduction of class inequality and the hidden bias of standardized tests (as discussed briefly in relation to IQ tests - see Stephen Jay Gould).

©2010 Sociological Images

* Positive Correlation: Defined by Timothy C. Urdan as: "A characteristic of a correlation; when the scores on the two correlated variables move in the same direction, on average. As the scores on one variable rise, scores on the other variable rise, and vice versa." (For more, see Urdan, T.C. (2005) Statistics in Plain English (2nd edition). Lawrence Erlbaum Associates, Inc.)

Note: Positive/negative correlations are found through "Correlational Analysis," which measures the strength of an association between two variables. Values range from +1.00 to –1.00. 

Rule of Thumb: Correlation should NEVER be confused with causation = they are very different things, and involve a very different set of calculations and often different research designs (methods, analysis, control groups, etc.). Causation causes correlation, but it is not necessarily the other way around. It is much easier to establish correlation than causation. And it is also very easy to confuse or inflate the significance of correlation - as seen in the media effects debates discussed in next week's Kline reading.

Monday, September 17, 2012

Monday, September 10, 2012

Sunday, September 2, 2012