Published online in Wiley Interscience (www.interscience.wiley.com). DOI: 10.1002/CJAS.94 Healthy and Safe Workplaces: Aspiring to Contributions from Multiple Administrative Disciplines
Bibliographic record
Abstract
national Labour Organization (ILO) office in 2001, reminds us that "the purpose of economic activity is to increase the well-being of individuals, and economic structures that are able to do so are more desirable than those that do not " (p. 9). Yet the ILO estimates that occupational illnesses and injuries result in approxi-mately 2.2 million deaths worldwide per year with over 264 million workplace injuries occurring annually, and over 700,000 workers a day suffering a workplace injury causing absence of three days or more (Hämäläinen, Takala, & Saarela, 2006). According to these statistics, modem economic activity is falling short of Stiglitz's desirability standard and requires more attention from academics and practitioners. Effective organizational action to promote worker well-being requires coordinated efforts among those who control resources and make decisions about how work is structured, as well as those who face the potential psychological and physical risks of work (Hofmann & Tetrick, 2003). There are many characteristics of organi-zations that may affect the way in which health and safety is managed and studied. For example, multina-tional companies (MNCs) experience high risks due to their geographically dispersed locations and operations in developing nations where national standards are less comprehensive compared to more developed countries. At the same time, small- and medium-sized enterprises Both authors acknowledge the financial support of the Workers Com-pensation Board of Manitoba and the Social Sciences and Humanities
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.780 | 0.711 |
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".