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Record W2611861339 · doi:10.29173/cais919

Numeracy Programming for Children in Canadian Public Libraries

2016· article· fr· W2611861339 on OpenAlexvenueaboutno aff
Samantha West, Michael B McNally, Dinesh Rathi

Bibliographic record

VenueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSI · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsNumeracyLiteracyRepertoireLibrary scienceChild careHumanitiesSociologyPolitical sciencePsychologyPedagogyComputer scienceMedicineArtPediatrics

Abstract

fetched live from OpenAlex

The proposed study was conducted to analyze thevariety of programs offered by public libraries inCanada for children to develop their literacy skills,particularly numeracy literacy skills. The findingsincluded in the paper are based on the thematicanalysis of information included on individuallibraries’ websites. Key findings suggest that althoughCanadian public libraries have a few numeracy skillsprograms in their repertoire, there is a need forgreater programming to develop these skills.L’étude proposée a été menée pour analyser lavariété de programmes offerts par les bibliothèquespubliques au Canada, destinés au développementdes compétences, en particulier en littératie et ennumératie chez les enfants. Les conclusions figurantdans l’étude sont basées sur l’analyse thématiquedes informations présentes sur les sites Webindividuels des bibliothèques. Les principalesconclusions suggèrent que si les bibliothèquespubliques canadiennes ont bien quelquesprogrammes de compétences en numératie dans leurrépertoire, il y a un besoin de programmationsupplémentaire pour développer ces compétences.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Scholarly communication
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.840
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
Scholarly communication0.0050.142
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.256
Teacher spread0.231 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the Annual Conference of CAIS / Actes du congrès annuel de l ACSISame topicLibrary Science and Information LiteracyFrench-language works237,207