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Record W2097813828 · doi:10.1177/1468798411401865

‘Literacy nooks’: Geosemiotics and domains of literacy in home spaces

2011· article· en· W2097813828 on OpenAlexaff
Sophia Rainbird, Jennifer Rowsell

Bibliographic record

VenueJournal of Early Childhood Literacy · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsBrock University
Fundersnot available
KeywordsSpace (punctuation)Agency (philosophy)LiteracyConstruct (python library)SociologyFamily literacyPsychologyPedagogyPublic relationsComputer scienceSocial science

Abstract

fetched live from OpenAlex

Conceptualizations of the home have changed, particularly in respect to children’s rearing and development. An increased awareness of early intervention in meeting a child’s learning needs has filtered down into the organization of space in homes. Maximizing learning opportunities by creating ‘literacy nooks’, which involves carving out interactive domains in the home, has become a way of asserting parental agency in their children’s development. The Parents’ Networks project is an Australian Research Council (ARC) funded project that focuses on how specific locales, such as commercial retail outlets, playgroups, libraries, health services and home spaces, have become networks of information sourcing and learning. This paper refers to a sub-project derived from this larger study that focuses specifically on the home space. We suggest that within the home space, parents construct learning environments for preschool children based on concepts of ‘good’ parenting. Four case studies of family homes in the US town of Greystone (pseudonym) are presented, exploring how space is arranged to produce an environment conducive to learning and development. In this article, we locate interview and observational data within space theory to posit how learning is mobilized within and across home environments.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.412
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.269
Teacher spread0.257 · 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 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

Citations11
Published2011
Admission routes1
Has abstractyes

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