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Record W1742897440 · doi:10.3233/wor-2011-1140

The health consequences of precarious employment experiences

2011· article· en· W1742897440 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueWork · 2011
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsInstitute for Work & HealthMcMaster UniversityPublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsOvertimeEarningsVulnerability (computing)Demographic economicsWork (physics)PensionJob securitySocial securitySurvey data collectionLogistic regressionPrecarious workBusinessEconomicsPsychologyLabour economicsMedicine

Abstract

fetched live from OpenAlex

OBJECTIVE: This study provides a test of a conceptual framework of the stress-related health consequences of "precarious" employment experiences defined as those associated with instability, lack of protection, insecurity across various dimensions of work, and social and economic vulnerability. METHODS: Data were drawn from the Canadian Survey of Labor and Income Dynamics (SLID), a nationally representative longitudinal labor-market survey (1999-2004). Logistic regression analysis estimated the impact of several dimensions of precarious employment on two health outcomes: low health status and low functional health. PARTICIPANTS: For each calendar year we selected a subsample of individuals with close ties to the labor-market--i.e., aged 25 to 54, not full-time students, and employed at least 9 months of the year. We excluded individuals who were self-employed, those in management-level positions, and individuals who reported less than good health at the beginning of the year. RESULTS: Certain work characteristics (low earnings, the lack of an annual wage increase, substantial unpaid overtime hours, the absence of pension benefits, manual work) predict an increased risk of adverse general and/or functional health outcomes. CONCLUSIONS: Proactive regulatory initiatives and all-encompassing benefits programs are urgently required to address emerging work forms and arrangements that present risks to health.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.271
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.126
GPT teacher head0.411
Teacher spread0.285 · 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