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Record W4239707053 · doi:10.32920/ryerson.14649603.v1

The missing links to developing holistic aboriginal early childhood services in Canada : a critical literature review

2021· preprint· en· W4239707053 on OpenAlexaffabout
Rachel Brophy

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsToronto Metropolitan UniversityEducation and Early Childhood Development
Fundersnot available
KeywordsTerminologyCLARITYIndigenousConsistency (knowledge bases)LiteracyIdentity (music)Early childhoodPsychologyPublic relationsSociologyPolitical scienceDevelopmental psychologyPedagogy

Abstract

fetched live from OpenAlex

This critical literature review explores the concepts of language, literacy and indigenous knowledge in relation to aboriginal early childhood development in Canada. Recognized is the urgent need for action in aboriginal communities and the connection between language, cultural identity and health. The review provides a synthesis of findings including a discussion of challenges, options and recommendations and a summary of themes. The critical content analysis is based in holistic principles of child development and identifies what is missing, ambiguous, and confusing within the literature and takes an advocacy stance on behalf of aboriginal children and families. The conclusion integrates ideas from the analysis into a statement of needs for future literature that will contribute to improving aboriginal child health and development. The most important findings are the need for clarity and consistency of terminology, the need to focus on children, and the need to include family voices in future literature.

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)0.026
metaresearch head score (Gemma)0.056
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.165
Threshold uncertainty score0.968

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0260.056
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0210.032
Science and technology studies0.0150.011
Scholarly communication0.0150.005
Open science0.0030.005
Research integrity0.0040.006
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 head0.016
GPT teacher head0.348
Teacher spread0.333 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2021
Admission routes2
Has abstractyes

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