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Record W2083089674 · doi:10.4018/ijsesd.2015040103

‘Stepping on the heads of our Gods'

2015· article· en· W2083089674 on OpenAlexaff
Yangji Doma Sherpa, A. John Sinclair, Thomas Henley

Bibliographic record

VenueInternational Journal of Social Ecology and Sustainable Development · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicTourism, Volunteerism, and Development
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPublic participationCitizen journalismTourismHydroelectricityParticipatory developmentAgricultureProcess (computing)Political sciencePublic relationsPublic administrationSociologyEnvironmental planningGeographyEngineeringLawArchaeology

Abstract

fetched live from OpenAlex

The Himalayan region of India is experiencing rapid development in tourism, agriculture, highway construction and hydroelectric dam construction. This research considered the role of the public both within and outside of development decision-making processes in these high mountain environments using the proposed Himalayan Ski Village (HSV) in Manali as a case study. The qualitative data revealed that there has been an extensive array of public participation activity related to the HSV project over approximately 10 years. Very little of this activity has evolved, however, through the formal decision-making process. Rather, most participation activities, such as general house meetings, objection letters, public rallies, court cases against the proposed project, and a religious congregation were instigated by the public to protest the proposed development. The findings also show that involvement in the participatory activities undertaken by the public and project proponent fostered instrumental and communicative learning outcomes.

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)0.003
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 score0.011
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0110.013
Scholarly communication0.0030.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.023
GPT teacher head0.310
Teacher spread0.287 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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