Les défis de gestion posés par la crise sanitaire de la COVID-19 : l'expérience d'un nouvel employé affecté au service de recrutement et de dotation dans le réseau de la santé du Québec
Bibliographic record
Abstract
« Cette recherche a pour but de mettre en lumière et d'analyser l'expérience d'un nouvel employé du service de recrutement et de dotation dans un établissement du réseau de la santé au Québec, Canada. Le tout prend place dans le contexte de la pandémie de la COVID-19, qui a eu une grande incidence sur le recrutement des ressources destinées à porter main-forte durant cette situation de crise. Nous étudierons alors plusieurs thématiques telles que la gestion des priorités et l'organisation du travail, mais aussi des théories sur les besoins de l'humain, en tenant compte du contexte particulier de la pandémie. En utilisant une méthodologie d'autopraxéographie issue du constructivisme pragmatique, nous tenterons de cerner les bonnes pratiques, mais aussi les lacunes, afin d'établir les bases qui pourraient mener à une meilleure planification du recrutement dans une situation d'urgence similaire. Nous conclurons cet ouvrage avec nos résultats qui démontrent, entre autres, l'importance de la communication en temps de crise, ainsi que la nécessité d'y prévoir l'organisation du travail, tout en s'assurant d'une mise en application progressive.-- Mot(s) clé(s) en français : changement, communication, créativité, crise, implication, pandémie, reconnaissance, recrutement, réseau de la santé, urgence. »-- \n« This research aims to highlight and analyze the experience of a new employee of the recruitment and staffing department, in an establishment of the health network in Quebec, Canada. All of this took place during the COVID-19 pandemic period and affecting the recruitment of resources intended to help out during this crisis situation.We will then study several themes such as the management of priorities, and the organization of work, but also theories on human needs, considering the particular context of the pandemic.Using an autopraxeography methodology derived from pragmatic constructivism, we will try to identify good practices, but also gaps in order to establish the bases that could lead to better recruitment planning, in a similar emergency situation. We will conclude this work with our results which demonstrate, among other things, the importance of communication during crisis, as well as the need to plan the organization of work, while ensuring a gradual implementation.-- Mot(s) clé(s) en anglais : Change, communication, creativity, crisis, emergency, health network, involvement, pandemic, recognition, recruitment. »--
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.022 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".