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Record W854653457 · doi:10.1300/j118v20n03_02

Informational Picture Books in the Library: Do Young Children Find Them?

2001· article· en· W854653457 on OpenAlexaff
Patricia A. Larkin‐Lieffers

Bibliographic record

VenuePublic Library Quarterly · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPicture booksRecreationFace (sociological concept)Variety (cybernetics)PreferencePsychologySchool libraryLibrary scienceVisual artsSociologyComputer scienceArtPolitical scienceSocial science

Abstract

fetched live from OpenAlex

Ten public libraries were surveyed to evaluate access for young children, aged 4 ½ to 6 years, to age appropriate informational picture books. Location of books, types of shelving, and displays were noted for both fiction and informational books, and unobtrusive observations of young children browsing were conducted in three of the libraries. The findings confirmed children's preference for books in eye level face front shelving in high traffic areas especially near the children's area seating; most children did not explore far from parents. Visits by children to hardcover fiction, paperback fiction, and paperback informational picture books, were balanced. However, hardcover informational picture books were missed due to less accessible locations, oversize shelving, and fewer displays. The role of accompanying parents in finding materials was pivotal. Improving access for young children to a wide variety of books in their public libraries supports both recreational and educational needs, and needs to be considered in library layout.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.014
GPT teacher head0.218
Teacher spread0.204 · 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 designObservational
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

Citations27
Published2001
Admission routes1
Has abstractyes

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Same venuePublic Library QuarterlySame topicChild Development and Digital TechnologyFrench-language works237,207