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Record W4403692028 · doi:10.4324/9781003388227-22

Meaningful Engagement in Canada

2024· book-chapter· en· W4403692028 on OpenAlexaboutno aff
Giuseppe Amatulli, Shona L. Nelson

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicNonprofit Sector and Volunteering
Canadian institutionsnot available
Fundersnot available
KeywordsPsychology

Abstract

fetched live from OpenAlex

In Canada, historical treaties were negotiated between the Crown and Indigenous Peoples to secure the peaceful settlement of lands and facilitate resource development. Treaty #8 is one of the historic treaties that assures its adherent First Nations of their rights to hunt, fish, and trap throughout the territory covered by the document. The treaty also allows for the taking up of lands by the provinces for settlement, mining, lumber, trade, or other purposes. While treaties in general, and Treaty #8 in particular, were intended to enable reconciliation, it has instead been the subject of several court cases. One of these cases is Yahey v. British Columbia ,, in which Chief Marvin Yahey, on behalf of Blueberry River First Nations (BRFN), successfully sued the province of British Columbia (BC) on the cumulative effects of industrial development on BRFN’s treaty territory. In the verdict, issued in June 2021, the Supreme Court of British Columbia ruled that by authorizing industrial development, the province of BC breached its obligation to BRFN under Treaty #8. As a result, the province could not continue to authorize activities that breach Treaty #8 and its unwritten promises without meaningfully engaging with the Nation. Within the context of meaningful stakeholder engagement, this chapter is a case study of Doig River First Nation (DRFN), a Treaty #8 First Nation with a shared history of land use with BRFN. In this contribution, it is explained how engagement for the purposes of resource development will need to shift post- Yahey from transactional consultation leading to project approval by the province, to meaningful community engagement with the goal of achieving First Nation consent and reconciliation.

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)0.005
metaresearch head score (Gemma)0.013
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 score0.200
Threshold uncertainty score0.927

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0580.014
Scholarly communication0.0190.005
Open science0.0030.016
Research integrity0.0070.012
Insufficient payload (model declined to judge)0.0480.004

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 head0.038
GPT teacher head0.275
Teacher spread0.237 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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