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Record W3093544936 · doi:10.3390/w12112957

Moving towards Effective First Nations’ Source Water Protection: Barriers, Opportunities, and a Framework

2020· article· en· W3093544936 on OpenAlexafffundabout
Rachael Marshall, Michele Desjardine, Jana Levison, Kim Anderson, Edward A. McBean

Bibliographic record

VenueWater · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsAssembly of First NationsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of OntarioRoyal Bank of Canada
KeywordsIndigenousGeneral partnershipFocus groupGovernment (linguistics)Environmental planningJurisdictionPolitical scienceEnvironmental resource managementQualitative researchBusinessPublic administrationGeographySociologyLawEnvironmental scienceEcologySocial science

Abstract

fetched live from OpenAlex

It is well known that watershed-based source water protection programs are integral to the provision of clean drinking water. However, the involvement of Indigenous communities in these programs is very limited in Canada, which has contributed to the vulnerability of Indigenous source waters to contamination. Through a partnership with an Anishinaabe community, this research aimed to identify challenges and opportunities for communities and practitioners to improve the protection of Indigenous source waters in the province of Ontario. The methodology followed the Indigenous research principles of relationship, respect, relevance, reciprocity, and responsibility. Interviews and a youth focus group were conducted with Indigenous community members and practitioners from industry, academia, non-governmental organizations (NGOs), and government. Analysis was conducted using an iterative process to develop codes and themes in the qualitative data analysis software NVivo. Results indicated that issues with scale, jurisdiction, the concept of source water protection, representation, funding, and capacity impact efforts to protect Indigenous source waters. Hopeful recent developments and upcoming opportunities were identified, and a water protection framework for First Nation communities in Ontario was developed in partnership with an Anishinaabe water protection committee. Recommendations are provided to multiple sectors for moving forward respectfully, and effectively, towards the protection of Indigenous waters.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.985
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.265
Teacher spread0.240 · 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

Citations22
Published2020
Admission routes3
Has abstractyes

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