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Record W2415233745 · doi:10.1177/084456211304500305

Impact of the Global Economic Crisis on the Health of Unemployed Autoworkers

2013· article· en· W2415233745 on OpenAlexaffvenueabout
Wally J. Bartfay, Emma Bartfay, Terry Wu

Bibliographic record

VenueCanadian Journal of Nursing Research · 2013
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsRecessionUnemploymentDepression (economics)AnxietyFinancial crisisGlobal recessionInterpretative phenomenological analysisEconomic slowdownFocus groupPsychologyMedicineQualitative researchDemographyDemographic economicsGerontologyPsychiatryEconomicsEconomic growthSociologyEconomySocial science

Abstract

fetched live from OpenAlex

A phenomenological investigation was undertaken to examine the effects of the 2008-09 global economic recession on the health of unemployed blue-collar autoworkers in the Canadian province of Ontario between September and November 2009. A total of 22 men and 12 women took part. Participants completed a quantitative demographic and financial questionnaire. The qualitative aspect of the study consisted of a phenomenological component comprising semi-structured focus group sessions lasting 2 to 2.5 hours. The number of years employed ranged from 2 to 31.7 with a mean of 15 +/- 8. Participants reported high levels of stress, anxiety, and depression; increased physical pain and discomfort; changes in weight and sexual function; and financial hardships, including inability to purchase prescribed medications. The authors conclude that unemployment associated with the global recession has negative health effects on autoworkers in Ontario.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.490
Threshold uncertainty score0.975

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.005
Scholarly communication0.0010.001
Open science0.0010.003
Research integrity0.0010.001
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 head0.195
GPT teacher head0.534
Teacher spread0.339 · 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 source (direct Gemma or distilled Codex), 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

Citations5
Published2013
Admission routes3
Has abstractyes

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