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Record W7133044973

Representations of Indigenous and Non-Indigenous Rural Ways of Being in Picture Books for Children

2022· other· en· W7133044973 on OpenAlexaboutno aff
Karen Eppley, Shelley Stagg Peterson, Jeffrey Wood

Bibliographic record

VenueTSpace · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsRuralityIndigenousRepresentation (politics)ScholarshipSocial representationNatural (archaeology)
DOInot available

Abstract

fetched live from OpenAlex

This critical content analysis examines representations of rural life in a sample of 52 picture books by Indigenous and non-Indigenous authors and illustrators. While the United States and Canadian governments use quantitative measures to designate rurality, in this study rurality is conceptualized more broadly as an interaction between geographical, cultural, and social characteristics. Three sets of findings about the representation of rural people in Indigenous and non-Indigenous picture books are offered: the representation of human-to-human relationships, the relationships between people and the natural world, and the problems and challenges faced by rural people in the books. While there is increasing attention within children’s literature scholarship about the importance of culturally relevant picture books and representations of diversity, less is understood about representations of rurality in children’s literature and still less is known about textual representations that engage the intersection of rurality and minoritized groups such as Indigenous peoples.

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)0.002
metaresearch head score (Gemma)0.009
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0030.005
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.014
GPT teacher head0.294
Teacher spread0.280 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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