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Record W2218236909 · doi:10.1080/14616688.2015.1122077

Beyond convention: reimagining indigenous tourism

2015· article· en· W2218236909 on OpenAlexaboutno aff
David Weaver

Bibliographic record

VenueTourism Geographies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousTourismConventionPolitical scienceGeographyLawEcologyBiology

Abstract

fetched live from OpenAlex

As a knowledge domain, contemporary indigenous tourism is framed in reference to cultures conventionally recognized as ‘indigenous,’ and engages this almost exclusively from a supply-side perspective. This paper reimagines indigeneity and indigenous tourism as embracing also the other 94% of global population. From a utilitarian perspective, this inclusion of ‘nonconventional indigenous people’ harbors opportunities to advance the sustainability agenda by reconnecting modern mainstream cultures, through personal exposure in dispersed settings, with ancestral roots and associated sustainable livelihoods. Such reconnections are framed as a form of re-indigenization that may be especially attractive to ‘travel promiscuous’ diasporic populations such as those found in the ‘settler’ countries of Canada, United States, Australia, and New Zealand. Articulation of this concept could be facilitated by existing knowledge domains and products in heritage tourism, rural tourism, and urban tourism, as well as sustainable tourism. Rather than usurping conventional indigenous efforts to re-indigenize and re-empower, it is contended that the nonconventional dimension can coexist with and even reinforce the latter, while enriching the dimensions of indigenous tourism as a dynamic knowledge domain.

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)0.009
metaresearch head score (Gemma)0.006
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: none
Teacher disagreement score0.017
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0110.037
Scholarly communication0.0130.018
Open science0.0020.016
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.037
GPT teacher head0.322
Teacher spread0.286 · 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

Citations18
Published2015
Admission routes1
Has abstractyes

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