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Record W2947466619 · doi:10.1177/1048291119850779

Workers’ Fight for Justice: A Retrospective Exposure Profile Study of the GE Factory in Peterborough, Ontario

2019· article· en· W2947466619 on OpenAlexaffabout
Robert DeMatteo, Dale Dematteo

Bibliographic record

VenueNEW SOLUTIONS A Journal of Environmental and Occupational Health Policy · 2019
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsCanada Auto Workers
Fundersnot available
KeywordsDenialHazardOccupational safety and healthMedicineEconomic JusticeFactory (object-oriented programming)Participatory action researchEnvironmental healthSociologyPsychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Occupational disease recognition is often hampered by lack of historical exposure data. This paper describes research documenting major chemical exposures of Canadian General Electric workers in a plant in Peterborough between 1945 and 2000. Workers’ experiences with diseases over forty years, and their frustration with the continual denial that these were work-related, drove this study. Researchers used qualitative methods, participatory action research, hazard mapping, and risk assessment. A report that incorporates this study’s findings documents extremely toxic exposures that placed Canadian General Electric workers at a disproportionate risk of occupational diseases. Since the report’s release, the Ontario Workplace Safety and Insurance Board reconsidered 233 previously denied claims in the light of “new evidence” and overturned one half of those it reviewed. The retrospective exposure profile methods used in this study may serve as a useful model for workers and their organization when plants close.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.030
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0090.002
Scholarly communication0.0020.001
Open science0.0010.002
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 head0.072
GPT teacher head0.428
Teacher spread0.356 · 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

Citations2
Published2019
Admission routes2
Has abstractyes

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