MétaCan
Menu
Back to cohort
Record W2484385532 · doi:10.1079/9781780644608.0246

A moral turn for mountain tourism?

2016· book-chapter· en· W2484385532 on OpenAlexaffabout
Lisa Cooke, Bryan S. R. Grimwood, Kellee Caton

Bibliographic record

VenueCABI eBooks · 2016
Typebook-chapter
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsThompson Rivers University
Fundersnot available
KeywordsTourismIndigenousPrivilege (computing)White privilegeColonialismMeaning (existential)Sense of placeEnvironmental ethicsGeographyEmbodied cognitionSociologyRepresentation (politics)Political scienceEconomic geographyGender studiesLawEcologyArchaeologyRace (biology)PoliticsEpistemology

Abstract

fetched live from OpenAlex

This chapter seeks to highlight mountain environments, which play host to tourism activities, as morally resonant spaces - spaces in which different meanings and values are asserted, contested, negotiated and resisted. It begins by exploring issues of representation in mountain tourism marketing, drawing on the example of ski tourism in the western USA to illustrate the way promotional discourse works to constitute mountains as geographies of exclusion and white privilege. Next, tourism development is considered as a colonial practice, exploring an example in which indigenous land claims are being overwritten by the counter land claims of a new corporate citizenry of 'lifestyle settlers' in British Columbia's first mountain resort municipality. Finally, the chapter explores canoe travel on the waterways of Canada's mountain environments as an embodied performance. These three explorations of moral geography aim to illuminate mountain areas as complex and layered spaces of meaning.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0060.014
Scholarly communication0.0060.004
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.045
GPT teacher head0.313
Teacher spread0.269 · 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 designTheoretical or conceptual
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

Citations2
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueCABI eBooksSame topicGeographies of human-animal interactionsFrench-language works237,207