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Record W3106926285 · doi:10.1097/ede.0000000000001304

The Serpent of Their Agonies

2020· article· en· W3106926285 on OpenAlexaff
Seth J. Prins, Sarah McKetta, Jonathan Platt, Carles Muntaner, Katherine M. Keyes, Lisa M. Bates

Bibliographic record

VenueEpidemiology · 2020
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of Toronto
FundersNational Institute on Minority Health and Health DisparitiesNational Institute on Drug Abuse
KeywordsSocioeconomic statusMental healthOddsOdds ratioPsychologyConfidence intervalOperationalizationMental illnessSocial stratificationCohortDemographyMedicineLogistic regressionPsychiatrySociologyPopulationInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Social stratification is a well-documented determinant of mental health. Traditional measures of stratification (e.g., socioeconomic status) reduce dynamic social processes to individual attributes downstream of mechanisms that generate stratification. In this study, we measure one process theorized to generate and reproduce social stratification-economic exploitation-and explore its association with mental health. METHODS: Data are from the 1983 to 2017 waves of the Panel Study of Income Dynamics, a nationally representative cohort study (baseline N = 3059). We operationalized "unconcealed exploitation" as the percentage of individuals' labor income they were hypothetically not paid for productive hours. We ascertained psychologic distress and mental illness with the Kessler-6 (K6) scale. RESULTS: We fit inverse probability-weighted marginal structural models and found that for each unit increase in unconcealed exploitation, psychologic distress increased by 1.6 points (95% confidence interval = 0.71, 2.5) on the K6 scale and the odds of mental illness tripled (odds ratio = 3.0, 95% confidence interval = 1.5, 6.1). Results were not driven entirely by overwork and were robust to different inverse probability-weighted estimation strategies and sensitivity analyses. CONCLUSIONS: Exploitation is associated with mental illness. Focusing on exploitation rather than its consequences (e.g., socioeconomic status), shifts attention to a structural process that may be a more appropriate explanatory mechanism, and a more pragmatic intervention target, for mental illness.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.644
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.242
GPT teacher head0.469
Teacher spread0.227 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations27
Published2020
Admission routes1
Has abstractyes

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