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Record W3034273189

Crimes against future inuit generations: Heavy metals and persistent organic pollutants (POPs)

2017· article· en· W3034273189 on OpenAlexaboutno aff
Konstantia Koutouki

Bibliographic record

VenueAustralian indigenous law review · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBiomagnificationIndigenousEnvironmental protectionPollutantArcticMercury (programming language)Environmental scienceEnvironmental healthEcologyBiology
DOInot available

Abstract

fetched live from OpenAlex

In the preamble of the 2001 Stockholm Convention on 'Persistent Organic Pollutants' we find the following acknowledgement: ' that the Arctic ecosystems and Indigenous communities are particularly at risk because of the biomagnification of persistent organic pollutants and that contamination of their traditional foods is a public health issue'. The vulnerability of the Indigenous populations of the Arctic to persistent organic pollutants ('POPs') was an impetus behind the 'Stockholm Convention' and although the relationship between POPs and the health of Indigenous peoples, especially children and the unborn, has been known for a very long time, there has been little in terms of legislation and public policy initiatives to diminish toxic chemicals in the food and natural environment of the Inuit. In addition to POPs, the children and adults of the Arctic communities are also disproportionately exposed to heavy metal contamination due to the presence of mercury, lead and cadmium, among others. In 2013, the 'Minamata' Convention on Mercury was adopted, under the auspices of the United Nations Environment Programme ('UNEP') and building on the 1998 to the 1979 Convention on Long-Range 'Transboundary Air Pollution on Heavy Metals'. Given the long-term effects on the Inuit of these substances, it begs the question whether this situation is in fact a crime against future generations of the Inuit.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.059
GPT teacher head0.352
Teacher spread0.294 · 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 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
Published2017
Admission routes1
Has abstractyes

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