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Record W2994735044 · doi:10.1080/14775085.2019.1702582

Similarities and differences in constraints and constraint negotiation among Japanese sport tourists: a case of masters games participants

2019· article· en· W2994735044 on OpenAlexaff
Eiji Ito, Shintaro Kono

Bibliographic record

VenueJournal of Sport & Tourism · 2019
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNegotiationTypologyConstraint (computer-aided design)TourismInterpersonal communicationAdvertisingSports tourismPsychologyPolitical scienceBusinessMarketingSocial psychologySociologyTourism geographyEngineeringLaw

Abstract

fetched live from OpenAlex

The purposes of this study were to examine (a) similarities and differences in constraints to and constraint negotiation for masters games (MG) participation, and (b) the relationships among constraints, constraint negotiation, and intention to participate in the World Masters Games 2021 Kansai, across international sport tourists, domestic sport tourists, and sport excursionists. An online survey was conducted with 449 Japanese people who participated in MGs within the last three years. Our results indicated that international sport tourists experienced higher levels of psychological, physiological, interpersonal, financial, tourism, commitment, MG-specific constraints than domestic sport tourists and sport excursionists, although physiological constraints did not differ between international and domestic sport tourists. Conversely, international and domestic sport tourists utilized tourism and MG-self-adaptation negotiation strategies more than sport excursionists. Lastly, constraints to and constraint negotiation for the past MG were not related to the intention of participation in the World Masters Games 2021 Kansai across the three groups. These results suggest that this typology of sport tourists – international, domestic, and excursionist – is an effective framework to understand constraints and negotiation as well as other behaviors and experiences of Japanese sport tourists.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.019
Threshold uncertainty score0.694

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.020
GPT teacher head0.276
Teacher spread0.256 · 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 teacher head, 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

Citations4
Published2019
Admission routes1
Has abstractyes

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