MétaCan
Menu
← Back to cohort
Record W2907044967 · doi:10.22215/etd/2016-11646

Towards a tailored vision of water security in the North: A case study of the Inuvialuit Settlement Region in the Canadian Arctic

2016· dissertation· en· W2907044967 on OpenAlexfundaboutno aff
Leah Ronayne

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
FundersAboriginal Affairs and Northern Development CanadaFisheries and Oceans CanadaHealth CanadaIndigenous and Northern Affairs CanadaTransport CanadaParks CanadaCanadian Patient Safety InstituteFisheries Joint Management Committee
KeywordsWater securityClimate changeGeographyContext (archaeology)ArcticSettlement (finance)Corporate governanceEnvironmental resource managementEnvironmental planningEnvironmental scienceWater resourcesBusinessOceanographyEcologyArchaeology

Abstract

fetched live from OpenAlex

Globally, the interest in water security is on the rise.Canada is fortunate to have an abundance of freshwater, and almost 20% of this is found in the Northwest Territories (NWT).Particular concern for the implications of climate change on the Mackenzie Delta, and the influence of land claims on water governance, make the Inuvialuit Settlement Region (ISR) in the NWT an important case study.Using a systematic literature review, thematic content analysis of 116 documents was conducted to understand how water is used and managed across scales in the ISR.A number of unique challenges emerged for the ISR in comparison to the Canadian water security context.Thus, a more tailored vision of water security needs to account for: cultural practices and well-being tied to uses of water/snow/ice, financial and capacity challenges related to remote locations, Indigenous land claims and governance complexities, ice as infrastructure, and high latitude sensitivities to climate change and contamination.

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)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.679

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0330.010
Scholarly communication0.0060.002
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.373
Teacher spread0.334 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2016
Admission routes2
Has abstractyes

Explore more

Same topicIndigenous Studies and Ecology→French-language works237,207→