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Record W2125933589 · doi:10.1123/jsm.26.2.113

Chronicling the Transient Nature of Fitness Employees: An Organizational Culture Perspective

2012· article· en· W2125933589 on OpenAlexaffabout
Eric MacIntosh, Matthew C. Walker

Bibliographic record

VenueJournal of Sport Management · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSubculture (biology)Perspective (graphical)ClubOrganizational cultureJob satisfactionPsychologyFunction (biology)Social psychologyMarketingPublic relationsSociologyBusinessPolitical science

Abstract

fetched live from OpenAlex

This study adopted an organizational culture perspective to examine the values and beliefs within fitness club operations and determine their influence on employees’ job satisfaction and intention to leave an organization. Consideration was also given to subcultures based on geographical location, organizational type, and job function to examine the ways in which organizations and employees may differ. Data were collected at three urban cities in Canada during a major fitness conference and tradeshow. The results from 438 employees confirmed the multidimensionality of the seven-factor instrument, in addition to illustrating the influence on job satisfaction and intention to leave. Further, the results revealed several dimensions were perceieved differently with respect to subculture. Findings connote the transient nature of jobs in the fitness industry which remains an immediate concern for managers in this field.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.005
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.321
Teacher spread0.305 · 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 designQualitative
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

Citations18
Published2012
Admission routes2
Has abstractyes

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