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Record W6906621021 · doi:10.17605/osf.io/f86wv

Vertebrate biodiversity on Indigenous-managed lands in Australia, Brazil, and Canada equals that in protected areas

2017· article· en· W6906621021 on OpenAlexaboutno aff

Bibliographic record

VenueOSF Preprints (OSF Preprints) · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicConservation, Biodiversity, and Resource Management
Canadian institutionsnot available
Fundersnot available
KeywordsBiodiversityThreatened speciesIndigenousGlobal biodiversityTreatyLand useHabitatConvention on Biological Diversity

Abstract

fetched live from OpenAlex

This is the data repository accompanying the publication 'Vertebrate biodiversity on Indigenous-managed lands in Australia, Brazil, and Canada equals that in protected areas' Abstract: Declines in global biodiversity due to land conversion and habitat loss are driving a ‘Sixth Mass Extinction’ and many countries fall short of meeting even nominal targets for land protection. We explored how such shortfalls in Australia, Brazil and Canada might be addressed by enhancing partnerships between Indigenous communities and other government agencies that recognize and reward the existing contributions of Indigenous-managed lands to global biodiversity conservation and their potential contribution to meeting international treaty targets. We found that Indigenous-managed lands were slightly more species rich than existing protected areas in all three countries, and in Brazil and Canada, that they supported more threatened species than existing protected areas or non-protected areas. Our results suggest that overall, Indigenous-managed lands and existing protected areas host similar levels of biodiversity in Brazil, Canada, and Australia. Partnerships with Indigenous communities that seek to maintain or enhance Indigenous land tenure practices on Indigenous-managed lands may therefore have some potential to ameliorate national and global shortfalls in land protection for biodiversity conservation using a mix of conventional protected areas and Indigenous-managed lands.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.952

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0580.049

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 head0.022
GPT teacher head0.230
Teacher spread0.207 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2017
Admission routes1
Has abstractyes

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