Albert Varela
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Albert Varela
@albertvarela.bsky.social
590 followers 820 following 11 posts
Lecturer in Quantitative Methods - School of Sociology and Social Policy, University of Leeds. 
Interested in measurement and analysis of job quality, poverty and social mobility.
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Reposted by Albert Varela
casmudde.bsky.social
After more than 10 years of “the Danish Model”, nativism is hegemonic in the country, the far right polls near level highs again, and the Social Democrats lost Copenhagen and poll at historic low.

European Social Democrats should look at the facts, not the myths!

Me in @theguardian.com
The ‘Danish model’ is the darling of centre-left parties like Labour. The problem is, it doesn’t even work in Denmark | Cas Mudde
This week’s local elections are the latest reminder that when social democrats move rightwards, they’re making a mistake, says academic and author Cas Mudde
www.theguardian.com
November 22, 2025 at 1:59 PM
Reposted by Albert Varela
deutschmann.bsky.social
New #openaccess study

We made >16,000 visa appointment requests at German embassies and consulates worldwide

Key finding: The poorer the country, the longer the wait time and the lower the chance to get an appointment.

"A time panelty for the Global South?"
shorturl.at/ZiAFb
Visas are a key tool for states to regulate incoming mobility from abroad, which can have ramifications for the establishment and perpetuation of global inequalities. In this article, we systematically analyze visa appointment wait times in German embassies and consulates worldwide. Using computational methods, we collect—and publish—fine-grained longitudinal data on the closest available appointment dates for various visa types, covering a total of 16,182 visa appointment requests. Our analysis reveals strong and systematic variance: the poorer the country a diplomatic mission is based in, the longer the wait time and the lower the chances of finding an available appointment (which ranges from almost 0 to 100 percent). We also argue that Germany’s system is quite opaque compared to other established immigration countries such as the U.S. These core findings raise important questions in light of current debates about global justice, legal pathways to migration, and efforts to attract foreign talent. Graph that shows that 44.1 percent of requests did not lead to an appointment that could be selected. For the 55.9 percent where an appointment was available the distribution of wait times follows a steep curve with short wait times in many cases and a long tail of few cases with very long wait times of up to 98 days. The average wait times and chances to find an appointment varied a lot between Germany's diplomatic missions. The latter range from almost 0 to 100 percent. This variance is not random. Rather, economic wellbeing (GDP per capita) is a key predictor of wait times and chances of finding an appointment. The poorer the country a German embassy/consulate is based in, the longer the wait time and the lower the chances of finding an appointment.
November 19, 2025 at 10:30 AM
Reposted by Albert Varela
juliusk.bsky.social
The electoral outcome most strongly linked to deprivation is not any party’s vote share, but turnout. Across almost all indicators, turnout is markedly lower in more deprived areas, with only barriers to housing & services and quality in the living environment showing weaker correlations.
November 3, 2025 at 8:41 AM
Reposted by Albert Varela
andrewjdbell.bsky.social
Pleased to see this out in print - detailing MAIHDA's desirable statistical properties.

"MAIHDA is especially valuable when inequalities are subtle or data for marginalised intersections are sparse - conditions common in practice"

journals.sagepub.com/doi/10.1177/...

@clarerevans.bsky.social
The Statistical Advantages of Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy for Estimating Intersectional Inequalities - George Leckie, Andrew Bell, Juan Merlo, SV Subram...
Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy (MAIHDA) is a multilevel regression approach grounded in intersectionality theory. I...
journals.sagepub.com
October 22, 2025 at 4:00 PM
Reposted by Albert Varela
quiquefm.bsky.social
We just published a new report synthesizing more than 7 years of research on the impact of digital technologies on employment in Europe carried out with my team in the JRC. Lots of evidence and ideas for discussion! #EconSky #sociology
@sergiotorrejon.com @lauranurski.bsky.social
Work in the Digital Era: How Technology is Transforming Work and Occupations
This report provides a comprehensive analysis of the impact of digital technologies on work and occupations in Europe, critically reassessing dominant narratives of mass unemployment and job polarisat...
publications.jrc.ec.europa.eu
September 12, 2025 at 5:03 PM
Reposted by Albert Varela
ronjasczepanski.bsky.social
Ever asked yourself how to detect and extract social groups from texts with computational social science? @haukelicht.bsky.social and me have a solution for you out at @bjpols.bsky.social. You can also find the pre-trained models on huggingface!
bjpols.bsky.social British Journal of Political Science @bjpols.bsky.social · Sep 1
NEW -

Detecting Group Mentions in Political Rhetoric A Supervised Learning Approach - cup.org/45WZppQ

- @haukelicht.bsky.social & @ronjasczepanski.bsky.social

#OpenAccess
BJPolS Abstract discussing a social science research method that uses text analysis for understanding group language patterns and political leanings, mentioning the use of British articles and generating new empirical insights.
September 1, 2025 at 3:46 PM
Reposted by Albert Varela
itsmccarthy.bsky.social
What do unions do? On average they make the members about $870k more wealthy over time, new findings at Social Forces show.
Abstract
September 1, 2025 at 6:20 PM
Reposted by Albert Varela
dingdingpeng.the100.ci
Ever stared at a table of regression coefficients & wondered what you're doing with your life?

Very excited to share this gentle introduction to another way of making sense of statistical models (w @vincentab.bsky.social)
Preprint: doi.org/10.31234/osf...
Website: j-rohrer.github.io/marginal-psy...
Models as Prediction Machines: How to Convert Confusing Coefficients into Clear Quantities Abstract Psychological researchers usually make sense of regression models by interpreting coefficient estimates directly. This works well enough for simple linear models, but is more challenging for more complex models with, for example, categorical variables, interactions, non-linearities, and hierarchical structures. Here, we introduce an alternative approach to making sense of statistical models. The central idea is to abstract away from the mechanics of estimation, and to treat models as “counterfactual prediction machines,” which are subsequently queried to estimate quantities and conduct tests that matter substantively. This workflow is model-agnostic; it can be applied in a consistent fashion to draw causal or descriptive inference from a wide range of models. We illustrate how to implement this workflow with the marginaleffects package, which supports over 100 different classes of models in R and Python, and present two worked examples. These examples show how the workflow can be applied across designs (e.g., observational study, randomized experiment) to answer different research questions (e.g., associations, causal effects, effect heterogeneity) while facing various challenges (e.g., controlling for confounders in a flexible manner, modelling ordinal outcomes, and interpreting non-linear models). Figure illustrating model predictions. On the X-axis the predictor, annual gross income in Euro. On the Y-axis the outcome, predicted life satisfaction. A solid line marks the curve of predictions on which individual data points are marked as model-implied outcomes at incomes of interest. Comparing two such predictions gives us a comparison. We can also fit a tangent to the line of predictions, which illustrates the slope at any given point of the curve. A figure illustrating various ways to include age as a predictor in a model. On the x-axis age (predictor), on the y-axis the outcome (model-implied importance of friends, including confidence intervals). Illustrated are 1. age as a categorical predictor, resultings in the predictions bouncing around a lot with wide confidence intervals 2. age as a linear predictor, which forces a straight line through the data points that has a very tight confidence band and 3. age splines, which lies somewhere in between as it smoothly follows the data but has more uncertainty than the straight line.
August 25, 2025 at 11:49 AM
Reposted by Albert Varela
cmpech.bsky.social
Check out my new article in the Journal of Organizational Sociology, where I examine how technology limits the autonomy of entry-level workers. I theorize two subtypes of technical control and discuss its implications for gender inequality
www.degruyterbrill.com/document/doi...
“The System Sucks”: Computer Programs and Technical Control in Entry-Level White-Collar Work
Researchers often examine how technology controls the labor of precarious workers while demonstrating the limits of technology on controlling professional workers. Drawing on a subset of 46 in-depth i...
www.degruyterbrill.com
August 13, 2025 at 2:15 PM
Reposted by Albert Varela
davidbuil.bsky.social
New how-to guide now available on the European Network for Open Criminology website. This time @asiermoneva.com shares advice on writing reproducible and readable analysis code. Highly recommended! esc-enoc.github.io/how-to/repro...
Write Reproducible and Readable Analysis Code – European Network for Open Criminology
Find out how to make your analysis code easy to share, understand, and reproduce.
esc-enoc.github.io
July 30, 2025 at 2:51 PM
Reposted by Albert Varela
jonathanhopkin.bsky.social
The outsourcing boom of the Major-Blair years saved money in the short run but left the state without the capacity to do anything but buy in services from canny private providers who have us over a barrel and are raking it in
July 23, 2025 at 7:27 AM
Reposted by Albert Varela
lisdata.bsky.social
🚨 Major release alert
We’re thrilled to launch lissyrtools v0.2.0 — our R package that makes working with LIS & LWS microdata simpler, faster, and clearer 📦
🧵 1/12
June 12, 2025 at 3:09 PM
Reposted by Albert Varela
haylesben.bsky.social
Interested in employment and social security research? Please follow the account below (we've moved from X and need to rebuild our following!)
June 12, 2025 at 11:44 AM
Reposted by Albert Varela
easystats.github.io
🆕 Introducing check_group_variation() in the {performance} #Rstats package! 🎉

This function makes it easy to checks if variables vary within or between levels of grouping variables.

Perfect for understanding and designing mixed models 🚀

easystats.github.io/performance/...

#stats #easystats
mlmRev::egsingle |> performance::check_group_variation( select = c("female", "grade", "math"), by = c("schoolid", "childid"), include_by = TRUE ) #> Check schoolid variation #> #> Variable | Variation | Design #> ------------------------------ #> childid | both | nested #> female | within | crossed #> grade | both | #> math | both | #> #> Check childid variation #> #> Variable | Variation | Design #> ----------------------------- #> schoolid | between | #> female | between | #> grade | both | #> math | both |
May 27, 2025 at 6:48 AM
Reposted by Albert Varela
dingdingpeng.the100.ci
Writing some paragraphs about odds ratio and, more generally, different scales in nonlinear models.

Any favorite articles on odds ratio?>
May 26, 2025 at 12:59 PM
Reposted by Albert Varela
jonathanhopkin.bsky.social
I’ll take the cutting migration idea seriously the day a politician actually outlines a serious budgeted plan for training British-born workers for the skills we’re short of, and housing them in the places where they’re needed. Until then it’s just the worst kind of blame-shifting propaganda
May 13, 2025 at 6:40 AM
Reposted by Albert Varela
youngvulgarian.marieleconte.com
christ, what a day to be an immigrant cursed with the ability to read
May 12, 2025 at 12:13 PM
Reposted by Albert Varela
andrew.heiss.phd
On the verge of declaring defeat with chatgpt in my asynchronous online dataviz class. Something changed this semester compared to past ones and SO MANY assignments are essentially 100% LLM output.
May 8, 2025 at 12:44 AM
Reposted by Albert Varela
strengejacke.de
I know it's getting boring when I keep posting easystats-stuff, but here's an example (vignette) how to "tweak" mixed models (demeaning) to get unbiased estimates: easystats.github.io/parameters/a...
I wouldn't call it "tweaking mixed models", because FE do the same. It rather about data...
Analysing Longitudinal or Panel Data
easystats.github.io
May 6, 2025 at 3:49 PM
Reposted by Albert Varela
vincentab.bsky.social
📚😅🎉

Yay!! I just submitted the complete manuscript of my upcoming book to the publisher!

Learn to easily and clearly interpret (almost) any stats model w/ R or Python. Simple ideas, consistent workflow, powerful tools, detailed case studies.

Read it for free @ marginaleffects.com

#RStats #PyData
Model to Meaning: How to interpret statistical models with marginaleffects for R and Python
April 10, 2025 at 7:06 PM
Reposted by Albert Varela
katymorris.bsky.social
New #dataviz in @sociusjournal.bsky.social

Did the occupational structure evolve in the same way in different parts of London between 1991 and 2021?

In short: no, it was very much A Tale of Two Cities

journals.sagepub.com/doi/10.1177/...
Sage Journals: Discover world-class research
Subscription and open access journals from Sage, the world's leading independent academic publisher.
journals.sagepub.com
March 31, 2025 at 11:50 AM
Reposted by Albert Varela
keonhison.bsky.social
📣NEW PUBLICATION
As a Korean who grew up in a low-income area in the 90s, I've long wondered why the gap between welfare laws and practice is rarely discussed.
doi.org/10.1177/1468...
Discrepancy of social insurance between laws and practices: Implementation challenges of maternity leave in 73 low- and middle-income countries - Keonhi Son, 2025
Although comparative welfare research has long criticized that the social insurance system in low- and middle-income countries (LMICs) fails to cover the under-...
doi.org
March 17, 2025 at 6:54 AM
Reposted by Albert Varela
sergiotorrejon.com
📢 Book Alert! "Global Trends in Job Polarisation and Upgrading: A Comparison of Developed and Developing Economies" is out!

Published by Palgrave Macmillan/ Springer, this volume examines global patterns of job creation at a global scale | 🔗 link.springer.com/book/10.1007... #EconSky #sociology
March 3, 2025 at 8:31 AM
Reposted by Albert Varela
christophscheuch.bsky.social
📢 New R package on CRAN: {owidapi}! Easily pull chart data from @ourworldindata.org into R: fetch data, explore datasets & embed charts in docs & Shiny apps (experimental). Feedback & ideas welcome 🙏
February 28, 2025 at 7:57 AM
Reposted by Albert Varela
andrew.heiss.phd
I really liked this idea of using a histogram as a legend in a choropleth map (since land isn't unemployed; people are), so I made a little guide to doing it with #rstats, {ggplot2}, and {patchwork}

www.andrewheiss.com/blog/2025/02...
February 19, 2025 at 5:58 PM