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Record W6991092474

First Nation capacity in Quebec to practice integrated water resource management

2011· dissertation· en· W6991092474 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2011
Typedissertation
Languageen
FieldEngineering
TopicParticle Accelerators and Free-Electron Lasers
Canadian institutionsnot available
Fundersnot available
KeywordsIntegrated water resources managementFirst nationParadigm shiftCapacity buildingResource (disambiguation)Water resources
DOInot available

Abstract

fetched live from OpenAlex

The emergence of Integrated Water Resource Management (IWRM) coincides with the growth of watershed associations in Québec. As a collective entity of stakeholders, these watershed associations use collaborative efforts to achieve IWRM. First Nations are often cited as priority stakeholders. Despite this 'priority' recognition, First Nations are rarely present in this new paradigm shift in water management. This is the case in Québec's Outaouais and Chateauguay watersheds. However, identifying First Nation capacity strengths and limitations provides a greater understanding as to their absence from IWRM participation. First Nation capacity to practice IWRM requires greater research. The purpose of this study is to apply an analytical framework to assess the overall capacity of two First Nation communities to practice IWRM in the province of Québec. The capacities of Kitigan Zibi and Kahnawà :ke First Nations were evaluated with respect to actor networks, information management, human resources, and technical, financial, and institutional dimensions. This study recommends that future Québec IWRM initiatives with First Nation collaboration need to be directed towards strengthening actor networks capacity and understanding the complexity of First Nation perspectives. In addition, study results indicate First Nations with limited financial capacity will experience reduced actor networks, information management, human resources, and technical capacity.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.024
GPT teacher head0.215
Teacher spread0.191 · 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 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

Citations0
Published2011
Admission routes1
Has abstractyes

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