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Record W2755805669

Environmental Groups Treading the Discursive Tightrope of Social License: Australian and Canadian Cases Compared

2017· article· en· W2755805669 on OpenAlexaboutno aff
Lyn McGaurr, Libby Lester

Bibliographic record

VenueeCite Digital Repository (University of Tasmania) · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsnot available
FundersUniversity of Tasmania
KeywordsTourismLicenseEcotourismAdversaryPolitical scienceEconomyPolitical economyBusinessSociologyEconomicsLaw
DOInot available

Abstract

fetched live from OpenAlex

Environmental nongovernmental organizations are often challenged to engage in economic debates. One response is to frame contested or protected areas and species as tourism assets. In this exploratory comparative study, we examine the discourse of environmentalists and members of the tourism sector in Australia and Canada for evidence they frame tourism as a social license to protect. We find environmentalists and sympathetic ecotourism operators frame successful activism in scenic places with a history of intense environmental conflict as an investment in tourism and the local economy. This makes a case for protection from extractive industries, but falters when the adversary is tourism itself.

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)0.005
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.695

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.012
Science and technology studies0.0370.014
Scholarly communication0.0070.003
Open science0.0030.010
Research integrity0.0040.004
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 head0.018
GPT teacher head0.206
Teacher spread0.188 · 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 designQualitative
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

Citations3
Published2017
Admission routes1
Has abstractyes

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