Bibliographic record
Abstract
anada is considered one of the most culturally diverse countries in the world, and for many of us, this diversity is a source of pride.Yet, it is not without its challenges.The implications for health system managers are clear -different languages and cultural perceptions can create tremendous barriers to communication and care delivery.Sensitivity to the values of diverse groups is a subject that is receiving increasing attention in the media as well as in professional publications.Ray Grady, who is President and CEO of the Evanston Hospital in Illinois, gave an inspiring presentation at a meeting of health educators and practitioners I attended last year.In this issue, we are pleased to have a modified version of his presentation.With passion, Mr. Grady describes the challenges for leaders in removing barriers and in reaffirming basic values and beliefs about multiculturalism.To supplement this paper, we have two Canadian commentaries.First Brenda Evans discusses the approach to multicultural leadership taken by the Vancouver/Richmond Health Board.Next, Elizabeth Hanna describes a more hands-on application of multicultural values in a specific patient care program.The events of September 11th were disturbing to everyone.For healthcare managers, along with the horror of the situation, there was also concern about the extraordinary challenges such a catastrophic event would place upon the system.In this issue, we are pleased to publish the emergency response strategy developed by Ontario's Ministry of Health and Long-Term Care.We would be equally pleased to publish strategies from other provinces.Recently, the Canadian Institute for Health Information released an extensive report, "Canada's Health Care Providers" (www.cihi.ca),that offers a comprehensive overview of this topic in Canada.In this issue, Jennifer Zelmer and Kira Leeb summarize key facts from the CIHI report that will enlighten the reader as to the depth of the human resource problem and offer insights for planners and policy makers.We will continue the focus on Canada's healthcare providers in an upcoming issue of the journal HealthcarePapers to be published in spring 2002.Watch for details on www.longwoods.com.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.248 | 0.147 |
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".