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Record W4252681239 · doi:10.1007/978-1-137-56994-3_1

Introduction

2015· book-chapter· en· W4252681239 on OpenAlexaff
Robert A. Stebbins

Bibliographic record

VenuePalgrave Macmillan UK eBooks · 2015
Typebook-chapter
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPerspective (graphical)PsychologyInterpersonal communicationField (mathematics)Social psychologyCore (optical fiber)Sociology of leisureSociologySocial scienceEngineeringComputer science

Abstract

fetched live from OpenAlex

Leisure plays a key role in positive psychology, though it would be difficult to reach this conclusion from the infrequency with which the idea surfaces in the field’s publications and intellectual discussions. This book shows how theory and research from the interdisciplinary field of leisure studies, more specifically from the serious leisure perspective (SLP), can be used to join the two fields, which have so much to offer each other. Thus, positive interpersonal relationships and positive emotional and cognitive states and processes — the stuff of positive psychology — are expressed or realized in myriad leisure activities (i.e., sets of particular behaviors). These activities are highly appealing, thereby providing their own motivational push. Leisure is defined and conceptualized as a kind of activity. General activities include the pursuit of certain core activities, which constitute powerful reasons for engaging in such leisure.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.583
Threshold uncertainty score0.831

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.4170.225

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 head0.041
GPT teacher head0.289
Teacher spread0.248 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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
Published2015
Admission routes1
Has abstractyes

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