MétaCan
Menu
Back to cohort
Record W2078448792 · doi:10.1080/01490400490461378

Recreational Conflict Is Affective: The Case of Cross-Country Skiers and Snowmobiles

2004· article· en· W2078448792 on OpenAlexaff
Joar Vittersø, Raymond Chipeniuk, MARGETE SKÅR, Odd Inge Vistad

Bibliographic record

VenueLeisure Sciences · 2004
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsRecreationFeelingPsychologySocial psychologyTest (biology)Quality (philosophy)Political scienceBiology

Abstract

fetched live from OpenAlex

The authors conducted a field experiment to test the assumption that subjective feelings are important in recreation conflict. During a weekend, cross-country skiers in a popular recreation area were assigned randomly to an experimental group who were exposed to an operating snowmobile, and a control group who were not exposed. Both groups completed a self-report questionnaire to provide information on their subjective experiences during their outing. The experimental group answered the questions five to ten minutes after encountering a snowmobile. Participants were not informed about the connection between the snowmobile and the investigation, and the questions regarding effects were answered before any clues were given about snowmobiles being an issue. Results showed that relative to the control group, skiers who encountered a snowmobile had their affective quality significantly reduced. Moreover, encountering a single snowmobile had an effect on participants' beliefs about the extent to which noise from snowmobiles disturbed the quality of ski-touring in general.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0030.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.029
GPT teacher head0.380
Teacher spread0.350 · 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

Citations50
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueLeisure SciencesSame topicRecreation, Leisure, Wilderness ManagementFrench-language works237,207