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Record W2033623589 · doi:10.2190/bpfg-x3me-lhta-6rpv

Job Insecurity and Health

2000· article· en· W2033623589 on OpenAlexaffabout
Peggy McDonough

Bibliographic record

VenueInternational Journal of Health Services · 2000
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsYork University
Fundersnot available
KeywordsHarmPsychologyMental healthConceptualizationFeelingDemographic economicsJob insecuritySelf-rated healthSocial supportSocial psychologyWork (physics)GerontologyEconomicsMedicine

Abstract

fetched live from OpenAlex

As employers respond to new competitive pressures of global capitalism through layoffs and the casualization of labor, job insecurity affects a growing number of workers. It appears to harm mental health, but less is known about its effects on physical health and health behaviors and the mechanisms through which it may act. The prevailing individual-centered conceptualization of job insecurity as the perception of a threat to job continuity precludes systematic investigation of the social patterning of its health effects. Analysis of data from a 1994 Canadian national probability sample of adults determined that high levels of job insecurity lowered self-rated health and increased distress and the use of medications, but had no impact on heavy drinking. The findings support one possible mechanism of action whereby job insecurity reduces feelings of control over one's environment and opportunities for positive self-evaluation; these psychological experiences, in turn, have deleterious health consequences. There is little evidence of social patterning of this relationship by gender, education, household income, age, marital status, and social support at work.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score0.892

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.463
Teacher spread0.408 · 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 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

Citations160
Published2000
Admission routes2
Has abstractyes

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