MétaCan
Menu
Back to cohort
Record W7017048154

Aboriginal Consultation for the Ontario Mining Act Modernization Process: Varying Perceptive on Whether the Consultation Process Works

2012· dissertation· en· W7017048154 on OpenAlexaboutno aff

Bibliographic record

VenueKnowledge Commons (Lakehead University) · 2012
Typedissertation
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsnot available
Fundersnot available
KeywordsModernization theoryIndigenousProcess (computing)DemocracyResource (disambiguation)DisadvantageNatural (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

Internationally, there is a trend for marginalized people to not be involved in natural resource management decision making that directly or indirectly affects them. This is the case for a majority of indigenous people around the world. Despite good intentions and efforts to include indigenous people through many different tools, including international declarations, national laws and policies, the resounding reality is that most are not involved in a meaningful manner (Baker and McLelland 2003 ; Bowie
\n2008; Sinclair and Diduck 2005; Whiteman and Mamen 2002). Nor do they have the capacity to challenge the status quo. The literature indicates many reasons and benefits to involve the public in decision making, such as strengthening of democracy and benefits of pluralism. Notwithstanding, the literature reveals that failed public involvement is the norm.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.597
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.029
GPT teacher head0.294
Teacher spread0.265 · 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.

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
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueKnowledge Commons (Lakehead University)Same topicComputational Physics and Python ApplicationsFrench-language works237,207