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Record W2979637385 · doi:10.29173/iasl7196

Reading communities in the School Library: the role of web 2.0 and social media

2016· article· en· W2979637385 on OpenAlexvenueno aff
Glória Bastos

Bibliographic record

VenueIASL Annual Conference Proceedings · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Digital Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsReading (process)PortugueseInteractivityContext (archaeology)Social mediaPromotion (chess)World Wide WebSchool libraryDiversity (politics)AppealComputer scienceSociologyPublic relationsPedagogyPolitical scienceGeography

Abstract

fetched live from OpenAlex

Literature for children and young people is taking advantage of the dynamics offered by digital world. Web tools and social media are now powerful resources to promote reading and children's literature among the new generations. These tools, due to its interactivity, open the door to new readers that find a new appeal when interacting with literature through these tools. Taking into account this context, school libraries cannot stay apart from the possibilities that these resources can offer for reading promotion. So, in Portuguese school libraries several projects are being developed, based on the dynamics that web 2.0 tools offer. In this paper we present some results of a project developed under a master's degree in School Libraries, at the Portuguese Open University. The results of these studies show a diversity of strategies that are followed by school libraries, trying to involve various actors (teachers, students, parents), thus contributing to the development of reading skills, with positive effects on motivation, reading and writing interests and competences.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.312
Threshold uncertainty score0.400

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.038
GPT teacher head0.285
Teacher spread0.247 · 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 teacher head, 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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