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Record W1800279298 · doi:10.3233/wor-131727

Policy on manager involvement in work re-integration: Managers' experiences in a Canadian setting

2014· article· en· W1800279298 on OpenAlexfundaboutno aff
Karin Maiwald, Agnes Meershoek, Angelique de Rijk, Frans Nijhuis

Bibliographic record

VenueWork · 2014
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchUniversity of TorontoUniversité de Sherbrooke
KeywordsFlexibility (engineering)Work (physics)Public relationsProcess (computing)BusinessHealth careQualitative researchSociologyPolitical scienceManagement

Abstract

fetched live from OpenAlex

BACKGOUND: In Canada and other countries, sickness absence among workers is a significant concern. Local return-to-work policies developed by both management and workers' representatives are preferred to tackle the problem. OBJECTIVE: This article examines how managers perceive this local bipartite agreed upon return-to-work policy, wherein a social constructivist view on the policy process is taken. METHODS: In-depth interviews were held with 10 managers on their experiences with execution of this policy in a Canadian healthcare organization. Interviews were transcribed verbatim and qualitative analyses were completed to gain deep insight into the managers' perspectives. RESULTS: Results show that the managers viewed themselves as a linchpin between the workplace and the worker. They did not feel heard by the other stakeholders, wrestled with worker's limitations, struggled getting plans adjusted and became overextended to meet return-to-work objectives. CONCLUSIONS: The study shows that the managers felt unable to meet the responsibilities the policy demanded and got less involved in the return-to-work process than this policy intended. RTW policy needs to balance on the one hand, flexibility to safeguard active involvement of managers and, on the other hand, strictness regarding taking responsibility by stakeholders, particularly the health care and re-integration professionals.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.396
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.358
Teacher spread0.334 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2014
Admission routes2
Has abstractyes

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