MétaCan
Menu
Back to cohort
Record W3037035471 · doi:10.3390/ijerph17124586

Molecular Decolonization: An Indigenous Microcosm Perspective of Planetary Health

2020· article· en· W3037035471 on OpenAlexaff
Nicole Redvers, Michael Yellow Bird, Diana Quinn, Tyson Yunkaporta, Kerry Arabena

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsIndigenousDecolonizationEnvironmental ethicsTraditional knowledgeColonialismPopulationSociologyGeographyEthnologyPolitical scienceEcologyBiologyLawArchaeologyPhilosophy

Abstract

fetched live from OpenAlex

Indigenous peoples are resilient peoples with deep traditional knowledge and scientific thought spanning millennia. Global discourse on climate change however has identified Indigenous populations as being a highly vulnerable group due to the habitation in regions undergoing rapid change, and the disproportionate burden of morbidity and mortality already faced by this population. Therefore, the need for Indigenous self-determination and the formal recognition of Indigenous knowledges, including micro-level molecular and microbial knowledges, as a critical foundation for planetary health is in urgent need. Through the process of Indigenous decolonization, even at the smallest molecular scale, we define a method back to our original selves and therefore to our planetary origin story. Our health and well-being is directly reflected at the planetary scale, and we suggest, can be rooted through the concept of molecular decolonization, which through the English language emerged from the 'First 1000 Days Australia' and otherwise collectively synthesized globally. It is through our evolving understanding of decolonization at a molecular level, which many of our Indigenous cultural and healing practices subtly embody, that we are better able to translate the intricacies within the current Indigenous scientific worldview through Western forms of discourse.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.109
GPT teacher head0.417
Teacher spread0.309 · 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 designObservational
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

Citations77
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Environmental Research and Public HealthSame topicClimate Change and Health ImpactsFrench-language works237,207