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Record W1607483039 · doi:10.3138/cbmh.29.2.283

Beginnings: The Occupational Health Program at the University of Alberta, 1984–1999

2012· article· en· W1607483039 on OpenAlexaffvenueabout
Tee L. Guidotti

Bibliographic record

VenueCanadian Journal of Health History · 2012
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGovernment (linguistics)SpecialtyHealth careOccupational medicinePopulationPolitical scienceMedicineOccupational safety and healthFamily medicineMedical educationManagementGerontologyPublic relationsNursingEnvironmental healthLawEconomics

Abstract

fetched live from OpenAlex

The Occupational Health Program (OHP) at the University of Alberta played an important and pioneering role in the specialty of occupational medicine in Canada between 1984 and 1999. Its history illustrates the opportunities and obstacles in one of the smallest and most unusual medical specialties in Canada. After an auspicious beginning in 1984, with support from industry, labour, government, and the university, the OHP encountered, but overcame, many problems subsequently as a result of underfunding, organizational placement, and, after changes in leadership, interference from the provincial government department responsible for occupational health. The history of the OHP illustrates problems of small training programs and the unique problems of occupational medicine but also its potential as a model for medical training out of hospital that responds to population health as well as individual care.

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: none
Teacher disagreement score0.056
Threshold uncertainty score0.406

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0090.001
Scholarly communication0.0030.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0210.004

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 head0.102
GPT teacher head0.403
Teacher spread0.301 · 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

Citations3
Published2012
Admission routes3
Has abstractyes

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