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Record W2143352271 · doi:10.20360/g2nc7t

Furrows in the field, or down in the jungle: re-membering domestic literacy in the early years

2012· article· en· W2143352271 on OpenAlexvenueno aff
Joan B. Simon

Bibliographic record

VenueLanguage and Literacy · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Education and Learning Practices
Canadian institutionsnot available
Fundersnot available
KeywordsLiteracySituatedJungleField (mathematics)SociologyProduct (mathematics)Social scienceEpistemologyPedagogyMedia studiesHistoryPhilosophyComputer science

Abstract

fetched live from OpenAlex

Embracing qualitative methods in an approach situated at the interface between education, social science and philosophy, the author offers a phenomenologically-oriented account of early family literacy, as experienced by a five year-old girl in Alsace, France. The paper seeks to enliven a fresh look at what we believe we see/understand and how we choose to disseminate this, thus it interrogates orthodoxies with regard to academic discourses and research methodology. The author proposes that to learn is to be in media res in the interminable flux of possibility. It is a never-ending story, which can only be told at a particular cross-section of time and place. Much follows from this insight, foremost among which is to accept that to attempt to understand and learn from learning, and to write academic ‘readings’ of learning, entails abandoning measurables and product-driven orientations in favour of processual ones.

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)0.018
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.018
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0120.046
Scholarly communication0.0110.013
Open science0.0010.010
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.419
Teacher spread0.388 · 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 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".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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