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Record W3009054679 · doi:10.3138/cjpe.69006

Section 35 Legal Framework: Implications for Evaluation

2020· article· en· W3009054679 on OpenAlexaffvenueabout
Pamela McCurry

Bibliographic record

VenueCanadian Journal of Program Evaluation · 2020
Typearticle
Languageen
FieldDecision Sciences
TopicEvaluation and Performance Assessment
Canadian institutionsCarleton University
Fundersnot available
KeywordsIndigenousGovernment (linguistics)General partnershipDutyPolitical sciencePublic administrationIndigenous rightsLawWork (physics)SociologyHuman rightsEngineering

Abstract

fetched live from OpenAlex

Abstract: Developments in Canada’s constitutional and legal framework since 1982 set the stage for the current Liberal government’s nation-to-nation policy, which recognizes Indigenous rights and seeks to build a relationship of respect and partnership through reconciliation with Indigenous peoples. These developments have important implications for those engaged in policy and program evaluations who are now called upon—not only by their own professional ethics but by the legal principles flowing from Section 35—to reimagine their approach and work as partners with Indigenous nations based on the recognition of Indigenous rights, reconciliation, and the Crown’s duty to act honourably in all of its dealings with Indigenous peoples. There are no off-the-shelf answers for how this can be done. Evaluation professionals will need to be guided by these key legal principles and the progressive view set out in the Liberal government’s Principles respecting the Government of Canada’s Relationship with Indigenous Peoples.

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)0.327
metaresearch head score (Gemma)0.487
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.327
Threshold uncertainty score0.939

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3270.487
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0060.009
Science and technology studies0.0170.037
Scholarly communication0.0400.019
Open science0.0130.011
Research integrity0.0290.021
Insufficient payload (model declined to judge)0.0160.003

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 head0.553
GPT teacher head0.591
Teacher spread0.038 · 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.

Study designNot applicable
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

Citations2
Published2020
Admission routes3
Has abstractyes

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