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Record W4231016101 · doi:10.24124/2012/bpgub1537

Impact of the Wellness Fitness program on employee absenteeism: a study of Prince George Fire Rescue: 2005-2011

2012· dissertation· en· W4231016101 on OpenAlexaffabout
Clayton Sheen

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsAbsenteeismPopularityGeorge (robot)Private sectorPublic relationsPsychologyApplied psychologyBusinessMarketingGerontologyManagementPolitical scienceMedicineSocial psychologyEconomic growthEconomicsComputer science

Abstract

fetched live from OpenAlex

Workplace wellness programs have been gaining popularity in many private organizations as a corporate strategy. The implementation of wellness fitness into the public sector has been a slower transition. Literature shows that the implementation has the potential to influence and improve various organizational factors such as absenteeism. The purpose of this project is to evaluate the hypothesis that the Prince George Fire Department Wellness Fitness program has reduced absenteeism. This project looks at the three possible categories of absenteeism and evaluates whether they have been reduced since the implementation of this program. The results found are that post Workplace Wellness implementation participants have less absenteeism. --P. iii.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.948
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.033
GPT teacher head0.425
Teacher spread0.392 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2012
Admission routes2
Has abstractyes

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