Call – Scientific Collaborator at the University of Neuchâtel 0.7 FTE (29.5 hours per week), 2 years

We’re hiring! Come and join us at the University of Neuchâtel:

Call for Application – Scientific Collaborator at the Swiss Forum for Migration and Population Studies, University of Neuchâtel
0.7 FTE (29.5 hours per week)

Two years appointment

The Swiss Forum for Migration and Population Studies intends to appoint one scientific collaborator. Potential candidates must hold a MA degree in Political Science, Sociology, Migration Studies, or a related discipline, and excel in research.

The research component of this position are part a SNSF project on explaining naturalized citizens’ political engagement. The project wants to analyze the political preferences of naturalized citizens, the drivers to become active participants in left and right wing parties and how they make sense of their background with regard to the party’s discourses. This will be measured based on content analyses and biographical interviews.

https://druedin.com/vacancies

1 RESEARCH ASSISTANT (15h/week, until 31 July 2019)

In the context of the NCCR ‘on the move’ (http://nccr-onthemove.ch/) we are looking for 1 research assistant to support research on the politicization of immigration in newspapers. We are now looking for one conscientious and reliable research assistant. You should be matriculated at the University of Neuchâtel, and will be expected to work relatively independently. You will search newspapers article in databases and code the contents of these articles following instructions. We offer somewhat flexible working hours (15h a week) and the ability to carry out some of the work from home. You will also be able to gain some insights in cutting-edge social science research. The position starts as soon as possible.

https://druedin.com/vacancies

Calling bull

This week we’ve had fun discussing how to better present results of quantitative analyses in graphs (hint: start by using graphs), and I figured I really should share the word of https://callingbull.org/ for those who are not aware of this excellent page (or the non-sanitized original here). In many ways the syllabus of this course reminded me of a course I took back then at Oxford where we were encouraged to think critically about research evidence (no, certainly not the “critical” that leads to “deconstructing” in the post-everything world). What I really like about the syllabus  Carl Bergstrom and Jevin West put together is that it goes well beyond just pointing out the nonsense out there, but they also provide useful tools and case studies. That’s what I try in my course, too.

Skill Specificity and Attitudes toward Immigration

I am very happy to announce a second paper published from our SNIS project on attitudes to immigrants: “Skill Specificity and Attitudes toward Immigration” by Sergi Pardos-Prado and Carla Xena out now in AJPS. It develops some of the key tenets of the SNIS project to new levels and provides a clean application.

Similar to what Marco Pecoraro concluded when looking at the risk of unemployment, Sergi and Carla come to the conclusion that economic competition theories cannot be dismissed. Here they focus on skills specificity and the ability to avoid competition with immigrant workers, and highlight that highly educated people are not immune to anti-immigrant attitudes.

Pardos‐Prado, S., & Xena, C. (2018.). Skill Specificity and Attitudes toward Immigration. American Journal of Political Science, Online First. https://doi.org/10.1111/ajps.12406
Pecoraro, M., & Ruedin, D. (2016). A Foreigner Who Does Not Steal My Job: The Role of Unemployment Risk and Values in Attitudes toward Equal Opportunities. International Migration Review, 50(3), 628–666. https://doi.org/10.1111/imre.12162

Turning R into SPSS?

I have written about several free alternatives to SPSS, including PSPP, Jamovi, and JASP. Bob Munchen has reviewed a few more options: Deducer, RKWard, Rattle, and the good old R Commander (in the screenshot on the left). We also find a review of Blue Sky Statistics. Blue Sky Statistics is another option for those seeking SPSS “simplicity” with R power underneath.

Blue Sky Statistics is available for Windows, and is open source. They make money from paid support. I note that it comes with a polished interface and this data editor that reminds us of Excel. I was very happy to see that Blue Sky Statistics offers many options for data handling, like recoding, merging, computing variables, or subsetting — that’s much better than what say jamovi offers at the moment.

The dialogs are quite intuitive if you are familiar with SPSS, and they can also produce R code. This is a feature we know from the R Commander, and ostensibly the aim is to allow users to wean from the graphical interface and move to the console. Nice as the idea is, it is defeated by custom commands like BSkyOpenNewDataset() that we don’t normally use.

The models offered by Blue Sky Statistics are fine for many uses — for those not living on the cutting edge. A nice touch are the interactive tables in the output, where you can customize to some degree.

Exciting as Blue Sky Statistics and other GUI are at first sight, I’m gradually becoming less excited about GUI for R. Probably the biggest challenge is the “hey, this is all text!” shock when you first open R (or typically Rstudio these days). Once you realize that the biggest challenge is to make the right choices and then interpret your results, you become less hung up about the “right” software. Once you realize that you’ll have to remember either way — where to click, or what to type — copying and pasting code fragments becomes less daunting. If you restrict yourself to a few basic commands like lm(), plot(), and summary(), R isn’t that difficult. Sure, when you come across idiosyncrasies because different developers use different naming conventions, R can be hard. But then, there are also the moments where you realize that there are so many ready-made solutions (i.e. packages) available and that with R you really are in control of your analysis. And the day you learn about replication and knitr, there’s hardly a way back.

One reason I kept looking for GUI was my MA students. I’m excited to see more and more of them choosing Rstudio over SPSS (they are given the choice, we’re currently use both in parallel)… so I there might be simply no need for turning R into SPSS.