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Record W4316924726 · doi:10.1289/isee.2022.o-sy-089

Indigenous community environmental challenges and needs

2022· article· en· W4316924726 on OpenAlexaboutno aff
Mi’sel Joe

Bibliographic record

VenueISEE Conference Abstracts · 2022
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousEnvironmental planningEnvironmental healthEnvironmental resource managementGeographyEnvironmental protectionMedicineEnvironmental scienceEcologyBiology

Abstract

fetched live from OpenAlex

Canadian Indigenous research in the past had had a history of deception. However, the European settlers later acknowledged the injustice committed in research and now actively engaged and respect their perspectives. Miawpukek First Nation (MFN) community in Newfoundland and Labrador is considered one of Canada's most well-administered Indigenous communities due to strong leadership and pragmatism in every developmental activities, including research. MFN has integrated indigenous perspectives in the health and wellbeing of the community. In the health care center, they did not put indigenous medicines into the modern-day clinic. They did not discourage it, but indigenous medicines were done through focusing on the land with hunting and gathering to make these indigenous medicines. There are many different kinds of health care. The Indigenous people prefer to walk through the woods to gather natural medicines. The community has integrated lighted walking trails, a gym, weight rooms and a community garden to help with their well-being and mental health. They are trappers and hunters and live off the land. Therefore, prefer this way of life over modern medicine when able. The climate change and planetary health crisis in the world is affecting everyone and everything, lands, oceans and animal migration are all being affected. The Indigenous communities used to do their fishing in the winter when the ice froze but because of the climate change there is no ice to fish on. The animals moved further south, for example, the polar bears to find food as well the fish farms are dying off. Everyone must play their part and work more towards green energy.

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, 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 score0.518
Threshold uncertainty score0.999

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 studies0.0100.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.104
GPT teacher head0.338
Teacher spread0.234 · 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
Published2022
Admission routes1
Has abstractyes

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Same venueISEE Conference AbstractsSame topicIndigenous Studies and EcologyFrench-language works237,207