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Record W2052050882 · doi:10.1080/14927713.2014.934030

The outdoor leisure behaviour of Moroccan public sector workers

2014· article· en· W2052050882 on OpenAlexvenueno aff
Catherine Bachleda, Ahlam Fakhar, Salma Slimani, Wafa Elgarah

Bibliographic record

VenueLeisure/Loisir · 2014
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsnot available
Fundersnot available
KeywordsNormativeStructural equation modelingTheory of reasoned actionNorm (philosophy)Theory of planned behaviorPublic sectorContext (archaeology)PsychologySample (material)Normative social influenceSocial psychologyLeisure timeDeveloping countrySociologyPolitical scienceGeographyEconomic growthEconomicsPhysical activityMathematicsManagement

Abstract

fetched live from OpenAlex

Do demographic variables directly impact attitude and subjective norm? This study sought to address this previously unanswered question by exploring whether income, education and gender influence attitude and subjective norm within the context of five leisure behaviours in Morocco. Employing an online survey method and structural equation modelling, results from a sample of 187 Moroccan public sector workers suggest that these demographic characteristics have no attitudinal or normative influence on participation in outdoor jogging, walking, biking, swimming and visiting natural parks. This finding appears to contradict the theory of reasoned action’s (TRA) early model assumptions. However, results do lend further support to the TRA’s sufficiency assumption and provide information about outdoor leisure behaviour in a developing country.

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)0.002
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 score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.030
GPT teacher head0.291
Teacher spread0.261 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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