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Record W2900807665 · doi:10.1111/dech.12456

The Ebb and Flow of Indigenous Rights Recognitions in Conservation Policy

2018· article· en· W2900807665 on OpenAlexfundno aff
Rebecca Witter, Terre Satterfield

Bibliographic record

VenueDevelopment and Change · 2018
Typearticle
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsnot available
FundersCanadian Institutes of Health Research
KeywordsHuman rightsIndigenousOperationalizationPolitical scienceIndigenous rightsEnvironmental planningPresumptionConservation biologyEnvironmental ethicsFundamental rightsEnvironmental resource managementLaw and economicsLawPublic administrationSociologyEconomicsGeographyEcology

Abstract

fetched live from OpenAlex

ABSTRACT At the 2003 World Parks Congress, diverse conservation actors called for the end of exclusionary approaches to conservation; recognition of customary forms of environmental protection; and restoration of losses to indigenous peoples whose lands were incorporated into protected areas without meaningful consent. A primary means to achieving such reforms has been the development of rights‐based approaches to conservation, expressed at the time as the better integration of human rights into the planning and management of protected areas. This article reviews the suite of publications that followed the 2003 Congress, each identifying the need for rights‐based approaches in conservation. All reviewed materials seek to operationalize human rights into conservation planning, but the review indicates a pattern of support for, then retreat from, and even a possible ‘backlash’ against, indigenous rights. The review also finds important differences in organizations’ ideas about who is responsible for protecting the environment versus who is responsible for protecting human rights. The authors draw from these findings a caution against the subversion of the original intention of rights‐based conservation to definitions that more fully serve conservation organizations’ own ends, based on the presumption that benefits (including rights) from environmental protection will eventually trickle down to people.

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)0.044
metaresearch head score (Gemma)0.051
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.044
Threshold uncertainty score0.234

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0440.051
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0040.027
Scholarly communication0.0110.020
Open science0.0020.006
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0090.000

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 head0.028
GPT teacher head0.215
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

Citations44
Published2018
Admission routes1
Has abstractyes

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