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Record W2789547934

Community-based assessments of change, contributions of Inuvialuit knowledge to understanding climate change in the Canadian Arctic

2001· dissertation· en· W2789547934 on OpenAlexvenueaboutno aff
Dyanna Riedlinger

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2001
Typedissertation
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeArcticGeographyEnvironmental resource managementEnvironmental planningEnvironmental scienceEcology
DOInot available

Abstract

fetched live from OpenAlex

An emerging theme in climate research is bridging the gap between Western science and Inuit knowledge of climate change to better understand Arctic climate change. This thesis is encouragement for this theme. Based in part on the collaborative research project 'Inuit Observations of Climate Change' (1999-2000) in Sachs Harbour, Western Canadian Arctic, I describe how local, land-based expertise and community-based assessments can provide observations, predictions and explanations of climate change at scales and in contexts currently underrepresented in climate change research. Firsthand experience working with local experts and scientists is used as a basis for a conceptual framework that explains how to find common ground between Inuvialuit traditional knowledge and Western science. This framework includes five areas of convergence in which traditional knowledge can complement scientific approaches to understanding climate change in the Canadian Arctic. These areas are: the contributions of traditional knowledge (i) as local scale expertise; (ii) as a source of climate history and baseline data; (iii) in formulating research questions and hypotheses; (iv) as insight into impacts and adaptation in Arctic communities; and (v) for long term, community-based monitoring. (Abstract shortened by UMI.)

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.713
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
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 head0.074
GPT teacher head0.329
Teacher spread0.254 · 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 designObservational
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

Citations11
Published2001
Admission routes2
Has abstractyes

Explore more

Same venueLibrary and Archives Canada (Government of Canada)Same topicIndigenous Studies and EcologyFrench-language works237,207