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Record W4285094313 · doi:10.32799/ijih.v17i1.36713

Indigenous Community Praxis and Programs during COVID-19

2022· article· en· W4285094313 on OpenAlexaffvenue
Denica Dione Bleau, Melanie Lansall

Bibliographic record

VenueInternational Journal of Indigenous Health · 2022
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Health and Education
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsIndigenousMental healthPandemicPraxisWork (physics)PsychologyEnvironmental healthEconomic growthCoronavirus disease 2019 (COVID-19)Public relationsNursingSocioeconomicsPolitical scienceMedicineSociologyPsychiatryEngineeringDiseaseInfectious disease (medical specialty)Law

Abstract

fetched live from OpenAlex

The COVID-19 Pandemic has substantially affected Indigenous communities. Deterrence of physical and mental health within Indigenous communities has been prevalent through unjust social, environmental and economic factors, due to pre-existing health conditions, unsustainable and overcrowded housing, limited health care and mental health services, and inadequate access to clean drinking water (Independent Auditor’s Report, 2021). These factors have resulted in exacerbated mental health and trauma symptoms (Arriagada, et. al., 2020). Indigenous communities have needed to adapt methods of attaining mental health and medical services, in order to maintain personal and communal wellbeing. We offer a summary of the delivery of two programs: The Medicine Keeper Wellness Program and Creative Corner Program, which were conducted in Northern Central Interior and Southern Indigenous communities by Indigenous social workers, to continue individual and community wellness. These programs navigated the barriers presented as a result of COVID-19 and the restrictions therein, to accessing social work and therapeutic services.

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)0.007
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0130.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.083
GPT teacher head0.462
Teacher spread0.379 · 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

Citations1
Published2022
Admission routes2
Has abstractyes

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