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Record W4318823551 · doi:10.1177/08295735221149225

Challenging Definitions of Student Success Through Indigenous Involvement: An Opportunity to Inform School Psychology Practice

2023· article· en· W4318823551 on OpenAlexaffabout
Velma ILLasiak Domoff, Yvonne Poitras Pratt, Michelle Drefs, Meghan Wick

Bibliographic record

VenueCanadian Journal of School Psychology · 2023
Typearticle
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMentorshipIndigenousBest practicePsychologyPedagogyLifelong learningEquity (law)School psychologyPublic relationsEngineering ethicsMedical educationPolitical scienceMedicineEngineering

Abstract

fetched live from OpenAlex

To achieve educational equity for Indigenous students, school psychologists need to consider the implications of using solely Westernized and Eurocentric educational standards of success. With current practices criticized as limiting and biased, a fitting alternative is the use of holistic frameworks of success aligned with Indigenous peoples’ perspectives on lifelong learning. This paper details a community-led process to define success for Indigenous youth in Aklavik, Northwest Territories inspired by the Canadian Council on Learning Inuit Holistic Lifelong Learning Model. Several key lessons, including the need for ensemble mentorship, emerged from this community-led and strengths-based project that can inform school psychologists seeking to better Indigenize their practice and work toward culturally aligned practices.

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)0.039
metaresearch head score (Gemma)0.033
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.956
Threshold uncertainty score0.206

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.033
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0170.047
Scholarly communication0.0160.018
Open science0.0030.025
Research integrity0.0030.011
Insufficient payload (model declined to judge)0.0030.000

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 head0.334
GPT teacher head0.502
Teacher spread0.167 · 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

Citations5
Published2023
Admission routes2
Has abstractyes

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