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Record W4253125782 · doi:10.24124/2019/59009

A critical legal geography of "Territory of Traditional Nature-Use" (TTP) formation in the Sakha Republic (Yakutia), Russia.

2019· dissertation· en· W4253125782 on OpenAlexfundno aff
Nicholas Parlato

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaNortheast Forestry UniversityUniversity of Northern British Columbia
KeywordsIndigenousPoliticsNormativeGeographyPolitical scienceCorporate governanceLawEcology

Abstract

fetched live from OpenAlex

In Russia’s largest region, the Sakha Republic (Yakutia), Indigenous (KMNS) leaders and communities representing five different cultural groups have succeeded in preserving traditional ways of life, and particularly nomadic reindeer husbandry, through the enormous political, social, and environmental changes of the past century. To ensure continued cultural survival, Indigenous leaders have developed a wide range of political and legal instruments, processes, and bodies within and without Russian governance structures. Key among these instruments is the “Territory of Traditional Nature-Use” (TTP), a geographically bounded legal-cultural landscape within which dozens of normative republican and federal acts, constitutional laws, and codices regulate and protect traditional land-use, socioeconomic organization, and ways of life.

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)0.002
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: Empirical
Teacher disagreement score0.048
Threshold uncertainty score0.096

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.013
Scholarly communication0.0040.002
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 head0.037
GPT teacher head0.372
Teacher spread0.335 · 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
Published2019
Admission routes1
Has abstractyes

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