Something every multi-national survey should do

This table is from the Afrobarometer website. You would think that every cross-national survey would have a page like this but I've never managed to track one down on some surveys I'll not mention, while others hide it so effectively it might as well not be there.

Your site can have as much on it as you like but before anything else the following three things should be linked prominently from the front page:

1. A table like the one above
2. Links to the original questionnaires for each country
3. Links to the raw data files, preferably as completely merged as possible

When working in different time zones is a good thing

I've recently been working with a team in a time zone seven hours away from mine. While this type of collaboration can often be a frustrating process of missed meetings and miscommunications, it has actually been surprisingly effective. In fact the vast majority of difficulties we have encountered have occurred due to the lack of being able to hold extended face to face meetings. However, given that everyone involved is spread across four locations this would have not been regular even if we were all in the same time zone.

So why has the time difference worked well in this instance? I think part of the success has been due to the type of work we are doing. We are currently writing a document together that requires revisions and reactions from team members. Generally, reading, commenting on and revising the document takes around three hours.

However, as anyone who has worked with multiple contributors knows, multiple people commenting at  the same time leads to a mess of incompatible suggestions and versions. This means you either have to deal with the mess of reconciling incompatible document versions or wait until each person finishes with their changes before someone else starts.

Being in different time zones actually improves this process because each side of the team tends to wake up to a new draft from the other side without having to spend working time waiting for it to arrive.

The key factor here is that the ideal length of independent work time (on this project) is fairly close in size to the time zone difference. If the ideal independent work time was a lot shorter, then there would be large stretches of underutilised time waiting for the other side to do their work. In this case, being in the same time zone would work much better.

The stretches of projects where long meetings are necessary fit better within a single time zone as they involve a continuous conversation backwards and forwards that gets greatly slowed down if each message has to wait a day for a reply.

Similarly, if the ideal length of independent work time was a lot longer than the time zone difference, then time zone wouldn't matter at all. For instance, the time zone differences between me and the journals I submit to is not at all relevant because the conversation with editors and reviewers tends to take place on the scale of weeks and months.

So what could this anecdote mean for the wider world? Well, it might suggest that we would expect information industries to be spaced around the world according to the size of tasks that are required to be done at each stage of a process. For instance, translation or editing agencies would be well placed several hours away from the sources of demand for these services.  An Indian editing firm might be able to offer overnight editing services for US firms.

I'd be interested to hear if anyone has looked into this more generally or if this mechanism holds outside of the particular case here.

Caveats:

•  I'm explicitly saying that the success of cross-time zone working is dependent on the type of task being performed and its requirement for parallel versus serial processing. I don't think that time zone differences are preferable in all cases.
• As usual this is written as a piece of speculation to open a debate and is clearly not a piece of carefully researched academic writing

Why emotional intelligence leads to poorer job performance: a hypothesis

The Atlantic has an interesting summary of the recent literature focusing on the negative effects of emotional intelligence. Essentially, emotional intelligence not only allows for better interpersonal relations and cooperation but also a greater ability to manipulate others.

One of the most interesting examples that the article gives is that, in non-emotional work (data analysis or car repair rather than counselling or teaching), there is actually a negative correlation between emotional intelligence and job performance (see here for the review article). The Atlantic article proposes that emotional intelligence distracts people from their work in these types of jobs: people spend their time reading their colleagues rather than their spreadsheets.

I have an alternate explanation that should probably be considered. While emotional intelligence may not make you better at low emotion jobs, it probably makes you more likely to be promoted or hired (conditional on prior job performance). If this is the case, then the negative correlation is simply the result of selection into jobs on the basis of emotional intelligence (due to bosses liking the employee or good interview performance).

Essentially a person with low emotional intelligence needs to be better at their job than a person with high emotional intelligence to get hired for the same position. It certainly fits better with my anecdotal observations than people being distracted by their emotions (surely people with more emotional intelligence need to expend less energy on reading those around them).

This hypothesis is also compatible with the finding that emotional intelligence is associated with better job performance in emotional work. In emotional work, emotional intelligence is a good signal for job performance (indeed it may be better than formal indicators), so promoting someone based on it probably improves the job/employee fit.

I've not read the literature in much depth so I'd be interested to hear if this hypothesis has been tested somewhere.

An idea for a more useful Google Trends

I've written a couple of articles (the second one is coming out in JEPOP some time soon but I don't have a link yet) about the limitations of using Google Trends data for social science research. The major issue is that many more search terms seem like plausible measures than actually turn out to correlate with public opinion. Search terms don't even necessarily work across different countries that speak the same language!

As a result, any use of these trends has to go through the process of matching up the data to equivalent survey data before it can be used validly.

But what if we didn't have to do all that?

One of the reasons I suspect the Google Trends sometimes don't match up as well as we would hope is that it counts searches not people. A handful of furiously searching journalists and politicos can drive the trend as much as widespread searching across the population. This means that issues may be ignored by 99% of the population but still result in a lot of Google searching.

So the graph above tracks what percentage of all searches in the United States were for the term "Syria" on different dates (these percentages are then scaled to a 1 to 100 index so we don't know the actual percentages).

This representative problem is easily solvable for Google. Simply report the trends for number of people searching for a term instead of the number of searches for a term. Google could simply offer us the option of tracking the percentage of people using Google on each date who searched for the term "Syria". Even if journalists search for Syria a thousand times, it will only count as one person.

It's not hard for Google to identify different people either. While there are some complexities to tracking an individual over time, Google has been building profiles on its users for a long time and even a measure of the number of unique IPs that searched for a term would go a long way towards solving this problem.

Having both of these settings as an option would give much greater insight into the breadth and depth of opinion on an issue.

It might even make offhand references to Google Trends as a proxy for public opinion a little more accurate.

Note: There are other reasons why Google Trends data might not match up to public opinion (see the papers) but this is certainly one major concern.

The Sociology Paper Title Generator

After noticing a trend towards quite generic naming of papers in sociology I decided to write a quick script to generate new ones. I took some components of some recent working papers and combined them at random. Initially, I thought it would generate some hilariously ridiculous sounding papers. More worryingly, it generates lots of very plausible sounding research topics. Here are the first 11 it generated:

A spatial analysis of cooperation and end of life care : in Eleven European countries 

The social determinants of Labour market outcomes and Class mobility : in Eleven European countries 

Revisiting Class mobility and part-time working : new perspectives for European research 

Measuring Fertility history and UK immigration policy : recent evidence from Germany 

Understanding employers' gendered hiring preferences and wives' earnings : assessing government responsiveness to public opinion 

Gender inequalities in part-time working and Employment change : recent evidence from Germany 

Long term trends in extreme right party membership and corruption : Does money matter? 

The effects of democracy on extreme right party membership and Class mobility : Does money matter? 

The social consequences of child mortality and Labour market outcomes : assessing government responsiveness to public opinion 

The effects of democracy on educational expansion and education :  revisiting the welfare state conundrum 

A spatial analysis of conflict and maternal education : in Eleven European countries

With the exception of Measuring Fertility history and UK immigration policy : recent evidence from Germany, none of these papers sound implausible and I really want to hear more about Long term trends in extreme right party membership and corruption. 


There's a serious side to this. Part of the problem with moving social science forwards is the difficulty in dismissing alternate explanations with limited data. If we really can connect any two variables together into a plausible hypothesis, how can we hope to dismiss all alternate explanations of any finding?