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Record W60407259

Comparing associate wages.

2009· article· en· W60407259 on OpenAlexaffabout
Darren Osborne

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldHealth Professions
TopicVeterinary Practice and Education Studies
Canadian institutionsCanadian Veterinary Medical Association
Fundersnot available
KeywordsNova scotiaWageGeneral partnershipCompensation (psychology)MedicineDemographyGeographyEconomicsPsychologyLabour economicsSociologyFinance
DOInot available

Abstract

fetched live from OpenAlex

Quebec took the top spot for the highest cost of living associate wages in 2008 with $5/h separating them from Nova Scotia — the province with the second highest wages. With a median cost of living adjusted hourly wage of $50.00, along with the lowest annual hours worked, Quebec was the place to be for salaried veterinarians in 2008. The 2008 Survey of Compensation and Benefits for Associate Veterinarians was distributed to 2713 associate veterinarians in Canada through a partnership between the Canadian Veterinary Medical Association and the provincial veterinary medical associations. Nationally, 842 veterinarians responded to the survey providing a 24% response rate and estimates that are accurate to +/− 2.7%, 19 times out of 20. Information on the survey applies to veterinarians in private practice only.

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)0.006
metaresearch head score (Gemma)0.033
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.437
Threshold uncertainty score0.870

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.033
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0600.007

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 head0.499
GPT teacher head0.483
Teacher spread0.016 · 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

Citations0
Published2009
Admission routes2
Has abstractyes

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