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Record W7026297329

Adapting to Environmental Change: Assessing the Vulnerability of Inuvialuit Communities to Infrastructure Risks Associated with Climate Change

2005· other· en· W7026297329 on OpenAlexaboutno aff

Bibliographic record

VenueUSC Research Bank (University of the Sunshine Coast) · 2005
Typeother
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsVulnerability (computing)Climate changeAdaptive capacityLivelihoodVulnerability assessmentPolitical economy of climate changeAdaptation (eye)ScholarshipEcological forecasting
DOInot available

Abstract

fetched live from OpenAlex

There is growing concern among Canadian Inuit about the impacts on the environment from global changes such as climate change. To date, the focus on this subject has been oriented on biophysical changes and impacts in the environment and little attention has been given to the potential vulnerability of community infrastructure. Research on vulnerability and adaptation to climate change has most often taken the form of impact studies with the purpose of estimating the physical impacts of climate change (Parry and Carter, 1998; Fankhauser et al., 1999). Adaptations were then considered as an end cost of climate change. However, it is now becoming increasingly recognized that initiatives to identify adaptation needs and to improve adaptive capacity start with an assessment of vulnerability of the system of interest (Ford and Smit, 2004). This draws on insights from political ecology scholarship which shows that access to resources, equity, livelihoods and the political and socio-economic conditions are important considerations in the assessment of adaptive capacity, and therefore vulnerability (Blaikie et al., 1994; Adger and Kelly, 1999; Bohle, 2001; Smit and Pilifosova, 2001; O’Brien et al., 2004).

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.470
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0060.001
Scholarly communication0.0000.000
Open science0.0010.005
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.209
GPT teacher head0.425
Teacher spread0.216 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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