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Record W7021009804

Northern Perceptions of Climate Change

2021· other· en· W7021009804 on OpenAlexaboutno aff

Bibliographic record

VenueYork University Digital Library (York University) · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsClimate changeCircumpolar starHuman settlementRacismPolitical economy of climate changeExtreme weatherFace (sociological concept)Resource (disambiguation)
DOInot available

Abstract

fetched live from OpenAlex

Inuit living in the circumpolar North have faced a number of rapid changes in the last century with the shift from nomadic to permanent settlements and the lingering negative effects of colonialism, now further challenged by the impacts of climate change. Currently, Iqaluit and other communities in Nunavut are at risk of running out of fresh water as they face factors including changing hydrological systems, increased population, ageing and inadequate infrastructure, and resource development (Bakaic & Medeiros 2017; Daley et al. 2014). Knowledge translation may be an essential tool for communicating these changes, both to Inuit and Western people, and better facilitate adaptation and mitigation strategies relating to climate change and water. This Major Project comprises three deliverables all with the aim of educating a different audience about issues including climate change, Inuit and Northern perspectives, and environmental racism. I have created 1) a children’s magazine article about monitoring climate change in the North using paleolimnology; 2) a journal article for Western academia that cautions about ignoring the socio-economic realities of Inuit daily lives; and 3) a magazine article for teenagers that talks about environmental racism and the North. Key findings from my research include that there is embedded racism within climate change, that there is a need for climate communication to be done in a respectful and culturally appropriate way, and that social issues were identified as equally important to climate issues for some people living in places of rapid environmental change.

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)0.002
metaresearch head score (Gemma)0.003
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: Other · Consensus signal: none
Teacher disagreement score0.856
Threshold uncertainty score0.286

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.004
Scholarly communication0.0050.004
Open science0.0000.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.016
GPT teacher head0.172
Teacher spread0.156 · 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
GenreOther

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
Published2021
Admission routes1
Has abstractyes

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