An Ailing Healthcare Organization
Bibliographic record
Abstract
Abstract Organizations in the healthcare sector are faced with the challenges of reducing costs, improving service quality and increasing work demands. The context of workforce shortages highlights the urgent need for action to ensure access to quality healthcare and services. The World Health Organization estimates that there is a shortage of nearly 6 million healthcare professionals worldwide. In May 2022, 8,700 full-time positions were vacant in the Quebec healthcare network. This situation calls for effective attraction, retention and loyalty strategies to attract and retain the necessary qualified personnel. Among the levers outlined in this chapter, the importance of equity, diversity and inclusion in personnel management is discussed. By fostering an inclusive environment, the organization benefits from access to a wider pool of skills, meets the expectations of under-represented groups and promotes cohesion with users. Retention of workers aged 55 and over is also highlighted as an important issue, notably by adapting their working conditions and recognizing their contributions. Organizations also benefit from tackling work overload, a source of stress and burnout, through sustainable prevention, involving good management, identification of risk factors and implementation of concrete actions. Finally, as key players in the implementation of these levers, managers, through their leadership and management practices, play a key role in promoting the attraction, retention and loyalty of human resources. It is therefore essential to ensure their well-being, so that they are in a position to adopt the behaviors needed to ensure the organization's longevity.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.269 | 0.151 |
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".