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Nick Diamond

@diamondn.bsky.social

scientist of human behaviour in government โ€” former academic ๐Ÿง  memory scientist https://scholar.google.ca/citations?user=PloV67gAAAAJ&hl=en

500 Followers  |  1,879 Following  |  14 Posts  |  Joined: 28.08.2023  |  2.377

Latest posts by diamondn.bsky.social on Bluesky

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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/...

11.08.2025 17:17 โ€” ๐Ÿ‘ 48    ๐Ÿ” 21    ๐Ÿ’ฌ 2    ๐Ÿ“Œ 2
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.

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...

02.04.2025 21:39 โ€” ๐Ÿ‘ 21    ๐Ÿ” 5    ๐Ÿ’ฌ 1    ๐Ÿ“Œ 0
Toronto shopping street

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 โ€œcar customers.โ€ Via @carltonreid.com www.forbes.com/sites/carlto...

25.03.2025 05:44 โ€” ๐Ÿ‘ 1911    ๐Ÿ” 616    ๐Ÿ’ฌ 39    ๐Ÿ“Œ 65

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.

13.03.2025 19:26 โ€” ๐Ÿ‘ 3    ๐Ÿ” 0    ๐Ÿ’ฌ 0    ๐Ÿ“Œ 0
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Sleep studies enter the real world - Nature Human Behaviour Memory for details fades over time, yet retaining the spatiotemporal associations inherent to our individual experiences may be adaptively relevant. Using an art tour as an experimental setting, Diamo...

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...

12.03.2025 20:35 โ€” ๐Ÿ‘ 4    ๐Ÿ” 2    ๐Ÿ’ฌ 0    ๐Ÿ“Œ 0
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 โ€œdata imperativeโ€ 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 inequalitiesโ€”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.

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 โ€œdata imperativeโ€ 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 inequalitiesโ€”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 variableโ€”understanding different variables and their distributions and relationships	Focus is on X โ€”understanding the relationship between X and Y, often with an emphasis on causality	Focus is on Y โ€”forecasting or estimating the value of Y based on X, often without concern for causal mechanisms
Names for variable of interest	โ€”		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 estimatingโ€”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	โ€”	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

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 variableโ€”understanding different variables and their distributions and relationships Focus is on X โ€”understanding the relationship between X and Y, often with an emphasis on causality Focus is on Y โ€”forecasting or estimating the value of Y based on X, often without concern for causal mechanisms Names for variable of interest โ€” 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 estimatingโ€”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 โ€” 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

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...

12.03.2025 17:36 โ€” ๐Ÿ‘ 139    ๐Ÿ” 26    ๐Ÿ’ฌ 6    ๐Ÿ“Œ 4
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Sleep studies enter the real world - Nature Human Behaviour Memory for details fades over time, yet retaining the spatiotemporal associations inherent to our individual experiences may be adaptively relevant. Using an art tour as an experimental setting, Diamo...

See a nice commentary here (thanks to @mschoenauer.bsky.social)

www.nature.com/articles/s41...

12.03.2025 15:15 โ€” ๐Ÿ‘ 7    ๐Ÿ” 0    ๐Ÿ’ฌ 0    ๐Ÿ“Œ 0

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. ๐Ÿง  oscillations matter.

Original ๐Ÿงต: bsky.app/profile/diam...

12.03.2025 15:15 โ€” ๐Ÿ‘ 18    ๐Ÿ” 7    ๐Ÿ’ฌ 1    ๐Ÿ“Œ 0
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Sleep selectively and durably enhances memory for the sequence of real-world experiences - Nature Human Behaviour How does sleep transform the way we remember our experiences? This study finds that sleep enhances memory for the order of events from an art tour, but not the details of the events. The sleep-related...

@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...

11.03.2025 19:24 โ€” ๐Ÿ‘ 49    ๐Ÿ” 22    ๐Ÿ’ฌ 0    ๐Ÿ“Œ 5
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A research agenda for encouraging prosocial behaviour on social media - Nature Human Behaviour Dรถrr et al. argue that research on social media has mainly focused on antisocial behaviours and call for more research on the ways in which social media platforms can empower prosocial behaviour.

In this Perspective, Dรถrr 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...

10.03.2025 20:21 โ€” ๐Ÿ‘ 6    ๐Ÿ” 3    ๐Ÿ’ฌ 0    ๐Ÿ“Œ 0

In this new preprint from our lab, we share exciting new findings on how โ€žSleep resolves competition between explicit and implicit memory systems!โ€œ ๐Ÿง  ๐Ÿ’ค ๐Ÿšจ

Kleespies, Paulus, et al.
@katjakleespies.bsky.social @philipppaulus.bsky.social

For a brief walkthrough, I refer you to Katjaโ€˜s post below!

26.02.2025 09:55 โ€” ๐Ÿ‘ 20    ๐Ÿ” 7    ๐Ÿ’ฌ 0    ๐Ÿ“Œ 0
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Human neural dynamics of real-world and imagined navigation - Nature Human Behaviour Seeber et al. studied brain recordings from implanted electrodes in freely moving humans. Neural dynamics encoded actual and imagined routes similarly, demonstrating parallels between navigational, im...

๐Ÿšจ New lab paper!๐Ÿšจ

A dream study of mine for nearly 20 yrs not possible until now thanks to NIH ๐Ÿง  funding & 1st-author lead @seeber.bsky.social

We tracked hippocampal activity as people walked memory-guided paths & imagined them again. Did brain patterns reappear?๐Ÿงต๐Ÿ‘‡

www.nature.com/articles/s41...

10.03.2025 16:52 โ€” ๐Ÿ‘ 270    ๐Ÿ” 81    ๐Ÿ’ฌ 10    ๐Ÿ“Œ 11
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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...

05.02.2025 16:39 โ€” ๐Ÿ‘ 69    ๐Ÿ” 32    ๐Ÿ’ฌ 1    ๐Ÿ“Œ 3

(1/4) Our new JEP:G paper dives into how moral values and misinformation spread on social media: media.mola-lab.org/file/1737039...

17.01.2025 03:31 โ€” ๐Ÿ‘ 26    ๐Ÿ” 14    ๐Ÿ’ฌ 1    ๐Ÿ“Œ 0
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Episodic and associative memory from spatial scaffolds in the hippocampus - Nature A neocorticalโ€“entorhinalโ€“hippocampal network model based on grid cell states recapitulates experimental results and reconciles the spatial, associative and episodic memory roles of the hippocampus.

New modelling of how episodic memory can arise from spatial mapping, just out in Nature:

www.nature.com/articles/s41...

16.01.2025 22:07 โ€” ๐Ÿ‘ 130    ๐Ÿ” 34    ๐Ÿ’ฌ 1    ๐Ÿ“Œ 2
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This week's cover and editorial @thelancet.bsky.social on mis- and disinformation's impact on public health
www.thelancet.com/journals/lan...

16.01.2025 23:38 โ€” ๐Ÿ‘ 232    ๐Ÿ” 95    ๐Ÿ’ฌ 6    ๐Ÿ“Œ 8
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.

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 fรผr 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...๐Ÿงตโคต๏ธ

09.01.2025 12:38 โ€” ๐Ÿ‘ 624    ๐Ÿ” 372    ๐Ÿ’ฌ 18    ๐Ÿ“Œ 115

perhaps another reason why econ and its related fields have been losing favor: epistemic supremacy of RCTs leads to incoherent policy recs

11.01.2025 16:56 โ€” ๐Ÿ‘ 94    ๐Ÿ” 24    ๐Ÿ’ฌ 8    ๐Ÿ“Œ 9
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โ€˜I canโ€™t go toe to toe with social media.โ€™ Top U.S. health official reflects, regrets. Xavier Becerra, who has led the Department of Health and Human Services, says federal agencies are outmatched in a world of โ€œinstantaneous information and disinformation.โ€

Trust in public health agencies has fallen and not recovered.

I asked Bidenโ€™s top health official what he thinks went wrong.

โ€œI canโ€™t go toe to toe with social media,โ€ HHS Secretary Xavier Becerra said.

12.01.2025 14:30 โ€” ๐Ÿ‘ 361    ๐Ÿ” 95    ๐Ÿ’ฌ 28    ๐Ÿ“Œ 21

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

07.01.2025 15:41 โ€” ๐Ÿ‘ 961    ๐Ÿ” 159    ๐Ÿ’ฌ 29    ๐Ÿ“Œ 22

If you feel that BlueSky is โ€œdifferentโ€œ 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 ๐Ÿงต follows!

1/

#scaling #NetSky #ComplexSystems ๐Ÿงช

08.01.2025 09:55 โ€” ๐Ÿ‘ 201    ๐Ÿ” 79    ๐Ÿ’ฌ 10    ๐Ÿ“Œ 8
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Meta ends fact-checking, drawing praise from Trump Meta CEO Mark Zuckerberg ended fact-checking on Facebook and Instagram in favor of community notes, calling the recent election a โ€œcultural tipping pointโ€ on free speech.

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

08.01.2025 02:03 โ€” ๐Ÿ‘ 289    ๐Ÿ” 106    ๐Ÿ’ฌ 37    ๐Ÿ“Œ 16

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.

07.01.2025 14:47 โ€” ๐Ÿ‘ 9    ๐Ÿ” 5    ๐Ÿ’ฌ 1    ๐Ÿ“Œ 0
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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...

07.01.2025 21:44 โ€” ๐Ÿ‘ 67    ๐Ÿ” 35    ๐Ÿ’ฌ 3    ๐Ÿ“Œ 1
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When are Fact-Checks Effective? An Experimental Study on the Inclusion of the Misinformation Source and the Source of Fact-Checks in 16 European Countries Despite increasing academic attention, several questions about fact-checking remain unanswered. First, it remains unclear to what extent fact-checks are effective across different political and med...

โ€œWe find that fact-checks are successful in debunking misperceptions. Moreover, this debunking effect is consistent across countriesโ€

Posting this key finding from our recent 16 country study.

For no particular reason today.

doi.org/10.1080/1520...

07.01.2025 21:25 โ€” ๐Ÿ‘ 168    ๐Ÿ” 94    ๐Ÿ’ฌ 0    ๐Ÿ“Œ 4
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Differences in misinformation sharing can lead to politically asymmetric sanctions - Nature We find that conservatives tend to share more low-quality news through social media than liberals, and so even if technology companies enact politically neutral anti-misinformation policies, political...

๐ŸšจIn Nature๐Ÿšจ
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...

07.01.2025 14:10 โ€” ๐Ÿ‘ 2730    ๐Ÿ” 1147    ๐Ÿ’ฌ 97    ๐Ÿ“Œ 156
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The Internet Is Worse Than a Brainwashing Machine A rationale is always just a scroll or a click away.

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...

06.01.2025 14:03 โ€” ๐Ÿ‘ 1487    ๐Ÿ” 466    ๐Ÿ’ฌ 57    ๐Ÿ“Œ 73
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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...

02.01.2025 12:55 โ€” ๐Ÿ‘ 146    ๐Ÿ” 53    ๐Ÿ’ฌ 4    ๐Ÿ“Œ 1
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Grief Makes Us Time Travelers (Gift Article) A neuroscientist studying memory, I used to believe time was linear. Then my mother had a stroke.

Honored that a piece I wrote made it to NYTimes. Itโ€™s about how my momโ€™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 ๐Ÿ™๐Ÿผ

www.nytimes.com/2024/12/20/s...

20.12.2024 15:04 โ€” ๐Ÿ‘ 484    ๐Ÿ” 91    ๐Ÿ’ฌ 49    ๐Ÿ“Œ 20
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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...

17.12.2024 19:50 โ€” ๐Ÿ‘ 435    ๐Ÿ” 166    ๐Ÿ’ฌ 18    ๐Ÿ“Œ 21

@diamondn is following 20 prominent accounts