Do ant colonies work like liquid brains? Check this great paper in @pnas.org led by @ceabcsic.bsky.social Pol Fernandez and F.Bartumeus that shows how to explain collective foraging by modelling ants as neural agents @jordipinero.bsky.social @frazambelli.bsky.social www.pnas.org/doi/10.1073/...
Data visualization depicting a stark increase in self-reported time spent alone in the canadian time use survey from 2005 to 2022. Density plot below depicts two distributions with very different peaks.
Day 2 of #30DayChartChallenge: Slope.
Canadians spent a *lot* more time alone in 2022 compared to 2005. But that comparison is especially stark for young Canadians.
Code: github.com/ivabrunec/30...
Toronto shopping street
Half of business owners on this Toronto street estimated that more than 25% of their customers arrived by car.
In fact, it was 4%.
And the % of customers who who walked or cycled? 72%.
Retailers routinely overestimate the # of “car customers.” Via @carltonreid.com www.forbes.com/sites/carlto...
Good q! We didn't measure that, but would love to.
Anyhow - you might expect emotion to enhance memory for the features of the artworks themselves (some sleep/consolidation theories predict this). Yet instead it was their order - unrelated to emotional content - that stuck, overnight and beyond.
Check out this brief review of our work by Jessica Palmieri and @mschoenauer.bsky.social
They do an excellent job of summarizing the main findings for a broader audience!
www.nature.com/articles/s41...
This essay provides an overview of statistical methods in public policy, focused primarily on the United States. I trace the historical development of quantitative approaches in policy research, from early ad hoc applications through the 19th and early 20th centuries, to the full institutionalization of statistical analysis in federal, state, local, and nonprofit agencies by the late 20th century. I then outline three core methodological approaches to policy-centered statistical research across social science disciplines: description, explanation, and prediction, framing each in terms of the focus of the analysis. In descriptive work, researchers explore what exists and examine any variable of interest to understand their different distributions and relationships. In explanatory work, researchers ask why does it exist and how can it be influenced. The focus of the analysis is on explanatory variables (X) to either (1) accurately estimate their relationship with an outcome variable (Y), or (2) causally attribute the effect of specific explanatory variables on outcomes. In predictive work, researchers as what will happen next and focus on the outcome variable (Y) and on generating accurate forecasts, classifications, and predictions from new data. For each approach, I examine key techniques, their applications in policy contexts, and important methodological considerations. I then consider critical perspectives on quantitative policy analysis framed around issues related to a three-part “data imperative” where governments are driven to count, gather, and learn from data. Each of these imperatives entail substantial issues related to privacy, accountability, democratic participation, and epistemic inequalities—issues at odds with public sector values of transparency and openness. I conclude by identifying some emerging trends in public sector-focused data science, inclusive ethical guidelines, open research practices, and future directions for the field.
Description Explanation Prediction General question What exists? Why does it exist? How can it be influenced? What will happen next? Focus of analysis Focus is on any variable—understanding different variables and their distributions and relationships Focus is on X —understanding the relationship between X and Y, often with an emphasis on causality Focus is on Y —forecasting or estimating the value of Y based on X, often without concern for causal mechanisms Names for variable of interest — Explanatory variable Independent variable Predictor variable Covariate Outcome variable Dependent variable Response variable Goal of analysis Summarize and explore data to identify patterns, trends, and relationships Estimation: Test hypotheses or theories and make inferences about the relationship between one or more X variables and Y Causal attribution: A special form of estimating—make inferences about the causal relationship between a single X of interest and Y through credible causal assumptions and identification strategies Generate accurate predictions; maximize the amount of explainable variation in Y while minimizing prediction error Evaluation criteria — Confidence/credible intervals, coefficient significance, effect sizes, and theoretical consistency Metrics like root mean square error (RMSE) and R^2; out-of-sample performance Typical approaches Univariate summary statistics like the mean, median, variance, and standard deviation; multivariate summary statistics like correlations and cross-tabulations t-tests, proportion tests, multivariate regression models; for causal attribution, careful identification through experiments, quasi-experiments, and other methods with observational data Multivariate regression models; more complex black-box approaches like machine learning and ensemble models
Table of contents Introduction Brief history of statistics in public policy Core methodological approaches Description Explanation Prediction The pitfalls of counting, gathering, and learning from public data Future directions References
New preprint! A general overview of stats in public policy research with this (oversimplified but still helpful) separation of methods into description, explanation, and prediction #policysky
HTML/PDF: stats.andrewheiss.com/snoopy-spring/
SocArXiv: doi.org/10.31235/osf...
Excited to see this big collaborative project out in the world @naturehumbehav.bsky.social !
Sleep actively enhances memory for the temporal sequence - but not sensory details - of our real-life experiences, even months-to-years later. 🧠 oscillations matter.
Original 🧵: bsky.app/profile/diam...
@diamondn.bsky.social et al. find that sleep enhances memory for the order of events from an art tour, but not the details of the events. The sleep-related advantage for sequences persists for over a year. @brianlevine.bsky.social
www.nature.com/articles/s41...
In this Perspective, Dörr et al. argue that research on social media has mainly focused on anti-social behaviours and call for more research on the ways in which social media platforms can empower pro-social behaviour.
https://www.nature.c
In this new preprint from our lab, we share exciting new findings on how „Sleep resolves competition between explicit and implicit memory systems!“ 🧠 💤 🚨
Kleespies, Paulus, et al.
@katjakleespies.bsky.social @philipppaulus.bsky.social
For a brief walkthrough, I refer you to Katja‘s post below!
🚨 New lab paper!🚨
A dream study of mine for nearly 20 yrs not possible until now thanks to NIH 🧠 funding & 1st-author lead @seeber.bsky.social
We tracked hippocampal activity as people walked memory-guided paths & imagined them again. Did brain patterns reappear?🧵👇
www.nature.com/articles/s41...
It's the post-"standard model" age! Our Preview of a fantastic new study from Yi Zhong's lab on the role of the hippocampus in updating remote memories. Fun putting this together with Ali Golbabaei.
authors.elsevier.com/a/1kZ4f3BtfH...
(1/4) Our new JEP:G paper dives into how moral values and misinformation spread on social media: media.mola-lab.org/file/1737039...
New modelling of how episodic memory can arise from spatial mapping, just out in Nature:
www.nature.com/articles/s41...
This week's cover and editorial @thelancet.bsky.social on mis- and disinformation's impact on public health
www.thelancet.com/journals/lan...
Graph that shows the sum of tweets and their impressions by members of the German Bundestag (Parliament), clustered by party. The blue AfD is a clear outlier with around 400 tweets and just under 40 million impressions.
In case you were wondering how things are going in Germany & on X, after Elon Musk announced his support for the far-right "Alternative für Deutschland" (AfD) in the upcoming Federal election:
The chart below shows sums of tweets x impressions by members of parliament over the past 7 days...🧵⤵️
perhaps another reason why econ and its related fields have been losing favor: epistemic supremacy of RCTs leads to incoherent policy recs
Trust in public health agencies has fallen and not recovered.
I asked Biden’s top health official what he thinks went wrong.
“I can’t go toe to toe with social media,” HHS Secretary Xavier Becerra said.
Basically my view is this: right now, the vast majority of voters are getting either some or all of their political information from a giant unregulated ambient media ecosystem, which only really shows them ideas that will excite or anger them, largely free of any fact-checking
If you feel that BlueSky is “different“ from X, the data supports you :)
Using a network of 15M users (56% of the platform) we find that the probability that the log-normal law is wrong wrt to the power-law is just ~7%
Why that matters? Pop 🧵 follows!
1/
#scaling #NetSky #ComplexSystems 🧪
Here's our full story on the Meta news today, which goes far beyond an end to fact-checking and heralds a wider pullback from content moderation as Zuckerberg repositions the company for the Trump era. Gift link: wapo.st/4h223hP
Community noteas take time to identify and attach, and only have any effect after this processes has completed---long after much of the exposure occurs. They also have lesser effect implicity on any content posted by large accounts as they get a *ton* of spread before a community note can be found.
Reflecting on the remarkable announcement from Meta today regarding content moderation. @sgonzalezbailon.bsky.social & I & team had a recent paper looking at the diffusion of (mis)information on Facebook during the 2020 election. A few reflections...
sociologicalscience.com/articles-v11...
“We find that fact-checks are successful in debunking misperceptions. Moreover, this debunking effect is consistent across countries”
Posting this key finding from our recent 16 country study.
For no particular reason today.
doi.org/10.1080/1520...
🚨In Nature🚨
Meta is dropping fact-checking to avoid anti-conservative bias- but is there actually evidence of bias?
We this test empirically & find that conservatives
* ARE suspended more
* BUT share more misinfo
So suspension isn't necessarily evidence of bias www.nature.com/articles/s41...
A big one today with @mikecaulfield.bsky.social. It's about Jan 6th but its really about trying to diagnose what precisely is broken about our information ecosystem and why everything feels so stuck. It's about how the internet is a justification machine. www.theatlantic.com/technology/a...
We have a new paper explaining all the ways you can use natural language processing to analyze text data in @natrevpsych.bsky.social
We provide user friendly recommendations for using NLP to ensure rigour and reproducibility
Here is a free link: www.nature.com/articles/s44...
Honored that a piece I wrote made it to NYTimes. It’s about how my mom’s stroke changed my connection to time, science, and nature. What a privilege to honor my mom in Modern Love.
Below is a gift link. Let me know your thoughts 🙏🏼
www.nytimes.com/2024/12/20/s...
Pleased to share the latest version of my paper with Arthur Spirling and @lexipalmer.bsky.social on replication using LMs
We show:
1. current applications of LMs in political science research *don't* meet basic standards of reproducibility...
