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Record W3208304192 · doi:10.1177/00221465211046359

Beliefs about Legality and Benefits for Mental Health

2021· article· en· W3208304192 on OpenAlexafffund
Laura Upenieks, Ioana Sendroiu, Ron Levi, John Hagan

Bibliographic record

VenueJournal of Health and Social Behavior · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsMental healthPrinciple of legalityEthnic groupStructural equation modelingSociologyPsychologyLife course approachSocial psychologySocial sciencePolitical scienceLawPsychiatry

Abstract

fetched live from OpenAlex

Research on mental health pays increasing attention to the influence of social institutions on subjective well-being over the life course. Yet little research has considered how belief in the promise of legal institutions may have beneficial effects for well-being. Through structural equation models of longitudinal data, our findings suggest that belief in the neutrality and fairness of legal institutions has salutary effects for mental health net of social and economic status and across individuals from a wide range of ethnic groups. By combining research in the sociology of mental health, cultural sociology, social psychology, and the sociology of law, we extend the emerging literature on the institutional determinants of mental health by including attention to law as one of the central organizing institutions of social life.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.518
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.081
GPT teacher head0.424
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2021
Admission routes2
Has abstractyes

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