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Record W6908429596 · doi:10.26181/29397476

Are Children Gaining a Sense of Place from Canadian Historical Picture Books?

2005· article· en· W6908429596 on OpenAlexaboutno aff

Bibliographic record

VenueLa Trobe University · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsnot available
Fundersnot available
KeywordsDepictionFeelingSense of placeCommon sensePsychology of selfSense of presence

Abstract

fetched live from OpenAlex

How do Canadian children come to understand and appreciate the uniqueness of Canada and of their Canadian-ness in the books they read? Young people must see themselves reflected in what they read and view so as to develop a sense of identity. Familiar emotions, activities, families, and surroundings are sensed through the depiction of the characters and story settings. To evolve a national identity, youngsters need to develop a sense of place, a feeling of 'This is where I belong'. It is crucial, therefore, that they see their communities, regions and country reflected accurately and authentically in literature. This study observes that many recent Canadian children's books lacked specific geographic content and place names. It suggests that only by increasing the number of cultural markers that Canadian children will be able to better identify their national landscapes and develop a sense of belonging to that landscape.

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 score0.063
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0080.006
Scholarly communication0.0080.004
Open science0.0020.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.008
GPT teacher head0.201
Teacher spread0.192 · 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
Published2005
Admission routes1
Has abstractyes

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