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Record W2056207560 · doi:10.1080/14775085.2013.838145

Environmental responsibility: internal motives and customer expectations of a winter sport provider

2013· article· en· W2056207560 on OpenAlexaff
Eric MacIntosh, Nic Apostolis, Matthew Walker

Bibliographic record

VenueJournal of Sport & Tourism · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsFraming (construction)Cognitive dissonanceSustainabilityMarketingPublic relationsBusinessAdvertisingPsychologySocial psychologyPolitical scienceGeographyEcology

Abstract

fetched live from OpenAlex

Mountain resorts that offer winter sporting opportunities are facing sustainability issues ranging from public criticisms to the deterioration of the natural environment. To gain perspective on the issue of environmental responsibility (ER) in this particular context, a mixed-method study regarding a single mountain resort was undertaken. The first research phase utilized qualitative methods to examine message framing and motivations for communicating ER to consumers. Findings demonstrate that framing ER was strategically motivated albeit marginally performed. The second research phase employed a scale development approach to investigate the revealed ER effects on consumer attitudes and expectations. Results demonstrated that consumers held moderate levels of environmental awareness and that their behavioral intentions were mildly impacted by the organizations ER initiatives. Overall, the study demonstrated that for organizational employees, framing environmental messages caused dissonance but consumers were influenced by the ER activities.

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)0.003
metaresearch head score (Gemma)0.007
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 score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.005
GPT teacher head0.233
Teacher spread0.228 · 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

Citations19
Published2013
Admission routes1
Has abstractyes

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