Bibliographic record
Abstract
Funded by the Canadian Institutes of Heath Research, the overall objective of the 2004 Canadian Campus Survey is to build understanding regarding the individual, social and environmental determinants of hazardous drinking. This preliminary report describes (1) the prevalence of alcohol use, other drug use, mental health and gambling problems among Canadian undergraduates interviewed in 2004, (2) relationships between these outcomes and student characteristics, and (3) whether such outcomes have changed since 1998. Methods A random sample of 6,282 full-time university undergraduates (41 % of eligible students) drawn from 40 universities completed questionnaires by mail (56%) or online (44%) during March and April 2004. Sixty-four universities with an enrolment of about 642,000 Canadian undergraduates, met the following criteria for inclusion: (1) had a Registrar, (2) had more than 1000 full-time degree undergraduates, (3) had students physically attend classes (i.e., online universities were excluded), (4) were publicly-funded, and (5) were non-military or non-theological. Of the 64 universities (69 campuses) that met the eligibility criteria, 40 (45 campuses) agreed to participate, representing completion rates of 63 % of universities and 65 % of campuses. The sample of 6,282 undergraduates averaged 22 years of age ranged in age between 16 and 65 years and included 2,248 men and 4,034 women. The sample comprised, 793 students were surveyed from universities in British Columbia, 513 from the Prairies, 2,107 from Ontario, 2,076 from Québec and 793 from the
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.214 | 0.089 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".