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Record W4234975066 · doi:10.24124/2015/bpgub1034

Understanding conceptions of land tenure in the Lake Babine Nation.

2015· dissertation· en· W4234975066 on OpenAlexfundno aff
Corbin Greening

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
FundersUniversity of Northern British Columbia
KeywordsStewardship (theology)Government (linguistics)Corporate governanceLegislationWork (physics)Land tenurePopulationSituatedPolitical scienceTreatyGeographyPublic administrationSociologyLawEconomicsManagementPoliticsEngineeringArchaeology

Abstract

fetched live from OpenAlex

Understanding Conceptions of Land Tenure in the Lake Babine Nation is about evolving values and the leaders who navigate them. The traditional territory of the Lake Babine Nation (LBN) is situated on Babine Lake, east of Smithers and north of Burns Lake - a community adjacent to the Lake Babine Nation's largest community by population. Ownership and stewardship of land in the LBN has been rapidly evolving since the imposition of the Indian Act and other government legislation in the early 20th century, forcing the Babine to adapt their social and land management techniques. With the prospect of self-governance on the horizon and pressure from the Federal and Provincial governments to adopt a system of land tenure based on private property, the LBN is at a crossroads. In this work, leaders from Chief and Council, the LBN Treaty Office, and the Hereditary Chiefs, expressed their vision for the management of the traditional territories, including traditional and western forms of ownership and stewardship, with an emphasis on collective responsibility. This work is designed to facilitate a discussion about the fundamental land values of the LBN and how they can be represented in the governance structure of a self-governing nation. --Leaf ii.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.934
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.019
Scholarly communication0.0060.007
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.057
GPT teacher head0.252
Teacher spread0.195 · 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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