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Record W4377021537 · doi:10.1080/16078055.2023.2213686

Adult Deviant Leisure Tendency Scale (ADLTS) – scale development study

2023· article· en· W4377021537 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWorld Leisure Journal · 2023
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPsychologyExploratory factor analysisScale (ratio)Social psychologyDimension (graph theory)Developmental psychologyPsychometrics

Abstract

fetched live from OpenAlex

Deviant or purple leisure associated with crime and criminal behaviour is notable as the non-innocent aspect of leisure. However, the deviant behavioural tendencies of leisure participants are an overlooked issue. The purpose of this study is to develop a scale to evaluate the deviant leisure tendencies of individuals. First, in-depth interviews and content analysis were conducted to generate the initial items. Second, exploratory factor analysis was conducted with 165 university students to determine the ideal number of items and to facilitate factor extraction. Third, confirmative factor analysis was employed to investigate 350 subjects on-site. Experimental evidence on psychometric qualities was uncovered through these processing steps and the Adult Deviant Leisure Tendency Scale (ADLTS) (one dimension and five items) was developed. As a result, it can be said that ADLTS is a valid and reliable measurement tool for individuals.

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.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.006

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 head0.026
GPT teacher head0.319
Teacher spread0.293 · 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