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Record W169171187 · doi:10.18584/iipj.2015.6.1.3

Finding Common Ground: A Critical Review of Land Use and Resource Management Policies in Ontario, Canada and their Intersection with First Nations

2015· review· en· W169171187 on OpenAlexaffvenueabout
Fraser McLeod, Leela Viswanathan, Graham S. Whitelaw, Jared Macbeth, Carolyn Dineen King, Daniel D. McCarthy, Erin Alexiuk

Bibliographic record

VenueInternational Indigenous Policy Journal · 2015
Typereview
Languageen
FieldEngineering
TopicMining and Resource Management
Canadian institutionsUniversity of WaterlooCanadian Celiac AssociationQueen's University
Fundersnot available
KeywordsTreatyIndigenousPublic administrationPolitical scienceCommon groundIntersection (aeronautics)Resource (disambiguation)Policy analysisEnvironmental planningEnvironmental resource managementEconomic growthGeographySociologyLawEconomics

Abstract

fetched live from OpenAlex

This article provides an in-depth analysis of selective land use and resource management policies in the Province of Ontario, Canada. It examines their relative capacity to recognize the rights of First Nations and Aboriginal peoples and their treaty rights, as well as their embodiment of past Crown–First Nations relationships. An analytical framework was developed to evaluate the manifest and latent content of 337 provincial texts, including 32 provincial acts, 269 regulatory documents, 16 policy statements, and 5 provincial plans. This comprehensive document analysis classified and assessed how current provincial policies address First Nation issues and identified common trends and areas of improvement. The authors conclude that there is an immediate need for guidance on how provincial authorities can improve policy to make relationship-building a priority to enhance and sustain relationships between First Nations and other jurisdictions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.913
Threshold uncertainty score0.853

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.293
Teacher spread0.249 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations26
Published2015
Admission routes3
Has abstractyes

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