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Cavan Bonner

@cavanvbonner.bsky.social

Doctoral student researching personality development at the University of Illinois at Urbana-Champaign. Self-regulation, adversity, and identity. www.cavanbonner.com

13 Posts568 Follower402 Folgt
Michael Inzlicht@minzlicht.bsky.social · 5mo ago

Qualitative coding 3,183 open-ended responses by hand would take 80+ hours. With an LLM-assisted workflow, Gino Carmona-Díaz and colleagues in Colombia did it in 10. ICC = .824. Full tutorial, prompts, and code are open access. link.springer.com/article/10.3...

An AI-powered research assistant in the lab: A practical guide for text analysis through iterative collaboration with LLMs - Behavior Research Methods

Analyzing texts such as open-ended responses, headlines, or social media posts is a time- and labor-intensive process highly susceptible to bias. However, large language models (LLMs) are promising to...

link.springer.com

Noam Ross@noamross.net · 7mo ago

NSF GRFP applicants (and mentors): Was your application Returned Without Review and deemed ineligible despite fitting in the allowed topics? 1) Write NSF 2) Write your Congressperson 3) CC us at grfp@grant-witness.us so we can compile + follow up Details and template at grant-witness.us/grfp-letter

Julia M. Rohrer@dingdingpeng.the100.ci · 8mo ago

I started reading up on the whole "loneliness pandemic" narrative because this seems like a literature where the age-period-cohort problem may be relevant (or maybe it isn't?). Here's data from Australia (HILDA), average agreement with the statement "I often feel very lonely" (SD of ca. 1.8).>

Average agreement with the statement "I often feel very lonely" plotted over time
Richard McElreath 🐈‍⬛@rmcelreath.bsky.social · 9mo ago

These openscience.nl grants are wonderful. Lavaan is a stand out in quality and impact. Open software supports so much research in academia and industry, but exists in some unincentivized gray zone. At the same time, so much software is poorly documented and tested. Fix with recognition and support

rogier kievit@rogierk.bsky.social · 9mo ago

I've used Lavaan almost every (work)day for 15 years, but this open source labour of love has never received proper institutional support. I'm delighted to be a small part of an 1.5M OpenScienceNL award, led by Jorgensen, to completely revamp and futureproof Lavaan www.openscience.nl/en/news/45-p...

Brendan Nyhan@brendannyhan.bsky.social · 10mo ago

"only about 5% of the variance in personality can be predicted from digital footprints, and personality‐tailored messages show negligible effects on behavior... When design and evaluation flaws are controlled, the combined end‐to‐end effectiveness of psychological targeting approaches zero."

The (In)Effectiveness of Psychological Targeting: A Meta‐Analytic Review

The use of psychological targeting—employing machine learning to predict consumer personality from digital footprints and subsequently tailoring persuasive messages—has emerged as a controversial yet...

onlinelibrary.wiley.com

Lukas Neville@lukasneville.com · 10mo ago

To be honest? Thank god. Because if advertisers can target on personality, this will be what it looks like (from 'Careless People')

"In April 2017, a confidential document is leaked that reveals Facebook is offering advertisers the opportunity to target thirteen-to-seventeen-year-olds across its platforms, including Instagram, during moments of psychological vulnerability when they feel “worthless,” “insecure,” “stressed,” “defeated,” “anxious,” “stupid,” “useless,” and “like a failure.” Or to target them when they’re worried about their bodies and thinking of losing weight. Basically, when a teen is in a fragile emotional state."
Brendan Nyhan@brendannyhan.bsky.social · 10mo ago

"only about 5% of the variance in personality can be predicted from digital footprints, and personality‐tailored messages show negligible effects on behavior... When design and evaluation flaws are controlled, the combined end‐to‐end effectiveness of psychological targeting approaches zero."

Brent W. Roberts@bwroberts.bsky.social · 10mo ago

Has conscientiousness really been in a free fall since 2014? A question that made us blog again: Has conscientiousness really been in a free fall since 2014?* floggingpvalues.blog/2025/10/22/h...

Has conscientiousness really been in a free fall since 2014?*

Brent W. RobertsA.J. WrightLena RoemerCavan Bonner Recently Burn-Murdoch reported in the Financial Times (FT) that since 2014 conscientiousness was in a “free fall” in younger p…

floggingpvalues.blog

Benedek Kurdi@benedek.bsky.social · 11mo ago

Preprint led by Salvador Vargas (on the job market!), with Chadly Stern, on stereotypes linking race & social class. We find a mean-level White–rich/Black–poor stereotype; the stereotype is strongest among third-group participants; and likely explained by social sampling: osf.io/preprints/ps...

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Pat Hastings@ophastings.bsky.social · 11mo ago

The GSS asked the same people about their childhood income rank three different times. 56% changed their answer, even though what was trying to be measured couldn’t change! We dig into this in a new article at @socialindicators.bsky.social. 

 doi.org/10.1007/s112... 🧵👇 (1/5)

Growing up Different(ly than Last Time We Asked): Social Status and Changing Reports of Childhood Income Rank - Social Indicators Research

How we remember our past can be shaped by the realities of our present. This study examines how changes to present circumstances influence retrospective reports of family income rank at age 16. While retrospective survey data can be used to assess the long-term effects of childhood conditions, present-day circumstances may “anchor” memories, causing shifts in how individuals recall and report past experiences. Using panel data from the 2006–2014 General Social Surveys (8,602 observations from 2,883 individuals in the United States), we analyze how changes in objective and subjective indicators of current social status—income, financial satisfaction, and perceived income relative to others—are associated with changes in reports of childhood income rank, and how this varies by sex and race/ethnicity. Fixed-effects models reveal no significant association between changes in income and in childhood income rank. However, changes in subjective measures of social status show contrasting effects, as increases in current financial satisfaction are associated with decreases in childhood income rank, but increases in current perceived relative income are associated with increases in childhood income rank. We argue these opposing effects follow from theories of anchoring in recall bias. We further find these effects are stronger among males but are consistent across racial/ethnic groups. This demographic heterogeneity suggests that recall bias is not evenly distributed across the population and has important implications for how different groups perceive their own pasts. Our findings further highlight the malleability of retrospective perceptions and their sensitivity to current social conditions, offering methodological insights into survey reliability and recall bias.

doi.org