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Record W2996066887 · doi:10.5864/d2019-027

Addressing Health Inequities in Environmental Public Health in Alberta

2019· article· en· W2996066887 on OpenAlexaffvenueabout
Michelle Kilborn, Jason Cabaj, Lynn Navratil, Angela Torry, Richelle Schindler

Bibliographic record

VenueEnvironmental Health Review · 2019
Typearticle
Languageen
FieldHealth Professions
TopicPublic Health Policies and Education
Canadian institutionsAlberta Health Services
Fundersnot available
KeywordsOperationalizationHealth equityPublic relationsEquity (law)Public healthSocial determinants of healthHealth promotionPolitical scienceBusinessEconomic growthMedicineNursingEconomics

Abstract

fetched live from OpenAlex

Environmental health related inequities can occur when environmental hazards or disasters disproportionally impact vulnerable populations, when environmental protection activities place a disproportionate burden on marginalized groups through a lack of inclusion or representation, and through creation of policies or programs that address only the immediate environment rather than the broader structural determinants that have created it ( Gore and Anita, 2013 ). Environmental public health (EPH) practitioners are well positioned to reduce inequities when they are empowered to include an equity lens in their work and identify opportunities to act on the social determinants of health (SDH). This focus group project identified ways in which public health inspectors in Alberta Health Services Calgary zone understand the concepts of equity and SDH as relevant to their work, revealed gaps in understanding and practice, and generated ideas to operationalize the integration of an equity lens into EPH practice. This project helps reinforce the importance of providing health equity education and opportunities for collaboration as a catalyst for action to integrate SDH and health equity into professional competencies and address organizational/operational barriers. Sharing these results will be helpful in moving towards fulfilling the key inequity-reducing role of EPH practice.

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)0.008
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.643
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0050.004

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 head0.175
GPT teacher head0.477
Teacher spread0.303 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreCommentary

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
Published2019
Admission routes3
Has abstractyes

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