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Record W3212184181 · doi:10.33137/tijih.v1i2.36052

Connections and Processes

2021· article· en· W3212184181 on OpenAlexaff
Gabriel Maracle

Bibliographic record

VenueTurtle Island Journal of Indigenous Health · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsTrent University
Fundersnot available
KeywordsIndigenousColonizationIdentity (music)Turtle (robot)SociologyLived experienceEcologyPsychologyAestheticsPsychotherapistBiologyArt

Abstract

fetched live from OpenAlex

This article focuses on the role of Indigenous identity and community connection in the healing journey. Healing from trauma and colonization are critical components to the lived experience of Indigenous people. This article outlines how Indigenous people in Turtle Island experience colonization and trauma. It will also discuss how the connection to our communities and our own identities are essential to addressing the spectre of trauma and colonization. This paper is rooted in the understanding that all of these concepts are not static but active processes. By actively engaging in our communities and our identities, we can gather strength and heal. By engaging with Indigenous communities, urban and reserve, our Indigenous identity is strengthened, which can help in healing from trauma and colonization.

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)0.004
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0110.026
Scholarly communication0.0110.012
Open science0.0020.014
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0200.002

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 head0.017
GPT teacher head0.319
Teacher spread0.302 · 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 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

Citations20
Published2021
Admission routes1
Has abstractyes

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