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Record W2411634127

Assessing Value: A Comprehensive Study of Impact Benefit Agreements on Indigenous Communities of Canada

2016· article· en· W2411634127 on OpenAlexaboutno aff
Drew Meerveld

Bibliographic record

VenueuO Research (University of Ottawa) · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousValue (mathematics)BusinessPublic economicsEconomicsComputer science
DOInot available

Abstract

fetched live from OpenAlex

Impact Benefit Agreements are formal contracts between Aboriginal bands and private industry outlining the obligations of each party throughout the business relationship. This mechanism for negotiation settlement is principally characterized as having no federal/provincial/territorial involvement. While Impact Benefit Agreements date back over 40 years, recent economic and social developments have led to an increased prevalence in the use of this type of agreement by the Canadian extractive industry. The economic data suggests that these types of agreements are beneficial to communities. Conversely, the socio-cultural outcomes may be seen as predominately negative. This is especially true for women as often marginalized actors within Aboriginal communities. Understanding the relative weight of each factor is underlain with considerations of sovereignty and the Canadian government’s duty to protect. Policymakers have a responsibility to create a negotiating environment which empowers the Aboriginal actors while allowing them the agency to develop in an autonomous manner.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.138
Threshold uncertainty score0.999

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.008
Science and technology studies0.0150.003
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.174
GPT teacher head0.335
Teacher spread0.161 · 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 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

Citations6
Published2016
Admission routes1
Has abstractyes

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