Bibliographic record
Abstract
A review of 154 Canadian EAPs found that 130 organizations had developed formal policies governing the program while 24 had not. Organizations with a policy were larger in size and were more likely to be unionized. They were also more likely to have had their EAP initiated by a joint labour-management committee and to use peer supports and internal resources to deliver EAP services. Of those EAPs without a policy, a disproportionate number had been developed during the 1990s. EAPs that had not developed a policy were also more likely to have begun exclusively by management and were more likely to rely on a third-party provider for clinical and administrative services. Of the 130 programs with EAP policies, 80 provided copies to be analyzed. Policies ranged in size from one to 31 pages with varying levels of comprehensiveness. Using the EAP Policy Best Practices Guidelines, policies scored between 5% and 75% with a mean of 36.7%. The introductory statement of principles, including discussions of the range of problems to be covered, confidentiality and union/management endorsement, was typically the strongest area of the policies. Areas that typically required enhancement were program development and EAP program roles. The comprehensiveness of the EAP policy was correlated with the size of the organization but not with program utilization. Public sector policies tended to be more comprehensive though only 26 of the 80 policies received a score of 50% or greater.
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 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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.018 | 0.044 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".