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Record W1974342508 · doi:10.3390/ijerph110201536

Investigating Environmental Determinants of Injury and Trauma in the Canadian North

2014· article· en· W1974342508 on OpenAlexafffundabout
Agata Durkalec, Chris Furgal, Mark W. Skinner, Tom Sheldon

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2014
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsGovernment of NunavutTrent University
FundersTrent UniversityNasivvik Centre for Inuit Health and Changing EnvironmentsArcticNet
KeywordsIncidence (geometry)ArcticEnvironmental healthInjury preventionOccupational safety and healthRisk factorMedicinePoison controlGeographyDemographyEcology

Abstract

fetched live from OpenAlex

Unintentional injury and trauma rates are disproportionately high in Inuit regions, and environmental changes are predicted to exacerbate injury rates. However, there is a major gap in our understanding of the risk factors contributing to land-based injury and trauma in the Arctic. We investigated the role of environmental and other factors in search and rescue (SAR) incidents in a remote Inuit community in northern Canada using a collaborative mixed methods approach. We analyzed SAR records from 1995 to 2010 and conducted key consultant interviews in 2010 and 2011. Data showed an estimated annual SAR incidence rate of 19 individuals per 1,000. Weather and ice conditions were the most frequent contributing factor for cases. In contrast with other studies, intoxication was the least common factor associated with SAR incidents. The incidence rate was six times higher for males than females, while land-users aged 26-35 had the highest incidence rate among age groups. Thirty-four percent of individuals sustained physical health impacts. Results demonstrate that environmental conditions are critical factors contributing to physical health risk in Inuit communities, particularly related to travel on sea ice during winter. Age and gender are important risk factors. This knowledge is vital for informing management of land-based physical health risk given rapidly changing environmental conditions in the Arctic.

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)0.005
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.447
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.100
GPT teacher head0.435
Teacher spread0.335 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations42
Published2014
Admission routes3
Has abstractyes

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