MétaCan
Menu
Back to cohort
Record W2782064495 · doi:10.22459/her.20.02.2014.01

Conservation Science Policies Versus Scientific Practice: Evidence from a Mexican Biosphere Reserve

2014· article· en· W2782064495 on OpenAlexaff
Gabriela Alonso-Yañez, Conny Davidsen

Bibliographic record

VenueHuman Ecology Review · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsBiosphereScientific evidenceScience policyEnvironmental ethicsPolitical scienceGeographyEnvironmental resource managementEconomicsEcologyBiologyEpistemologyPublic administrationPhilosophy

Abstract

fetched live from OpenAlex

This paper interrogates the activities, perspectives, and positions of scientists conducting research in Sierra de Huautla Biosphere Reserve, Mexico. Biosphere reserve conservation models are specifically designed for a sustainable integration of social and natural environments, a mandate that relies on both natural and social scientific research to improve conservation of nature and human well-being. Seen through the analytical lens of a social worlds/arenas framework, integrative scientific research in this particular case proves to be challenging in practice and fraught with paradoxes and contradictions. The findings suggest that academic and institutional factors (funding, publication avenues, and scholarly status) force, or at least strongly invite, scientists to pursue academic research agendas which, in fact, may conflict with or override the researchers' own commitments to meaningful conservation research work and interventions. This case highlights structural concerns over biosphere reserve-specific governance issues in Mexico, and integrative human-environment scientific practice in conservation in general.

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)0.017
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.997
Threshold uncertainty score0.091

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0030.004
Scholarly communication0.0050.003
Open science0.0010.003
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 head0.065
GPT teacher head0.326
Teacher spread0.261 · 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.

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

Citations7
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueHuman Ecology ReviewSame topicConservation, Biodiversity, and Resource ManagementFrench-language works237,207