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The Role of Fulbright Program in Focusing on Canadian and U.S. Environmental Health Issues

2018· article· en· W2991028190 on OpenAlexaboutno aff
David F. Goldsmith

Bibliographic record

VenueISEE Conference Abstracts · 2018
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousContext (archaeology)Political scienceEnvironmental protectionGeographyEcology

Abstract

fetched live from OpenAlex

Background: Scholars from Canada and U.S. have collaborated with the Fulbright Program to address environmental issues of mutual interest in both countries. Studies of climate change in the artic and health of Indians/First Nations illustrate the role of Fulbright investigators have had on these issues.Context: Climate change has had drastric impacts on Artic communities in Alaska and in northern Canadian villages. Researchers from Canada and U.S., spurred on by Fulbright, have brought investigators together to measure the extent of sea level rise and methods to respond to these changes, including rebuilding indigenous communities away from degraded shores. Scholars from U.S. and Canada have also collaborated on means and methods to address environmental degradation, wildlife habitats, and Indian/Fist Nation health impacts. Examples include indigenous diets, obesity, and diabetes, adolescent suicide, alcoholism, violence towards women, and childhood accidents.Future collaboration: Canada and U.S. share industrial interests in fishing, agriculture, and mining/petroleum extraction, all of which have high rates of workplace accidents, trauma, and death. Additionally, all three industries have very high indigenous participation and concern. Fulbright programs, including active participation from corporate scientists, can be vehicles for developing innovative transnational initiatives to reduce accident injury and death as well as methods for environmental remediation. We need greater professional interest and applications by environmental scientists to Fulbright as well as new environmental health programs directly sponsored by Fulbright to provide a higher profile for future offerings.Conclusion: The Fulbright program has enabled Canadian and American academics and leaders to collaborate across our borders to tackle serious environmental issues. New problems, such as lowering workplace injury rates, need to be added for future scholars to tackle.

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)0.021
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.111
Threshold uncertainty score0.802

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.040
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0400.014
Scholarly communication0.0120.006
Open science0.0050.014
Research integrity0.0100.014
Insufficient payload (model declined to judge)0.0300.002

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 head0.032
GPT teacher head0.361
Teacher spread0.329 · 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 designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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