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Record W2948823881 · doi:10.11645/13.1.2513

Shaking up story time

2019· article· en· W2948823881 on OpenAlex
Bartlomiej A. Lenart, Carla J. Lewis

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Information Literacy · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsPhilosophy for ChildrenComputer sciencesortProcess (computing)Mathematics educationMultimediaPedagogyPsychologyInformation retrievalProgramming language

Abstract

fetched live from OpenAlex

While the Philosophy for Children (P4C) method has been adopted within classrooms by individual teachers and into some school systems by schoolboards, public and school libraries, the ideal users of this sort of programming, have been slow to recognise the benefits of this didactic methodology. This is particularly surprising given that the P4C method integrates perfectly with traditional story-time orientated programming. Not only is the integration of P4C into story-time sessions virtually seamless (as it does not aim to replace, but rather strives to enhance story-telling), but it might also help reinvigorate a well-established feature of library programming with an aim to develop 21st-century information literacy competencies. This paper examines the case for the P4C method, explains the process of integration of the P4C method with traditional story-time, and highlights the potential benefits of incorporating Philosophy for Children in public and school library programming.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.953
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.009
GPT teacher head0.314
Teacher spread0.305 · 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