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Record W2313194142 · doi:10.1093/ps/81.5.618

Survey of Pacific Egg and Poultry Association Scholarship Recipients (1965-1994)

2002· article· en· W2313194142 on OpenAlexaboutno aff
Francine A. Bradley, B.A. McCrea

Bibliographic record

VenuePoultry Science · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsScholarshipTrade associationAssociation (psychology)Political scienceMedicinePsychologyBusiness

Abstract

fetched live from OpenAlex

The Scholarship and Research Foundation of the Pacific Egg and Poultry Association, a West Coast trade association, began awarding scholarships in 1965. The scholarship program was established as a means of rewarding high scholastic performance and encouraging careers in the poultry industries. A survey was conducted of the 1965 to 1994 recipients. During the 30-yr period, the association awarded 513 scholarships. Alumni association offices in western Canada and the United States were able to provide current mailing addresses for 312 of the recipients. A letter was sent to each former recipient requesting information on postdegree career paths. Responses were received from 104 or 33.3% of the individuals. Initial career choices and current occupations were tabulated. Broad occupational choices were categorized as poultry, agriculturally related nonpoultry, nonagricultural, still in school, or unknown. Poultry-related careers were categorized by more specific job definitions: live production, allied industry, extension, research/teaching faculty, and veterinary medicine. The poultry industries attracted 52.9% of the recipients for their first postdegree job. Currently, 50.0% of the recipients are employed by the poultry industries. Of those, 36.5% are in live production, 19.2% in allied industry, 5.8% in extension, 17.3% in research/teaching, and 21.1% in veterinary medicine.

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)0.002
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 score0.021
Threshold uncertainty score0.348

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.094
GPT teacher head0.273
Teacher spread0.178 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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