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Parents shine by their presence in school: making visible the absence in the cogenetic theory

2022· article· en· W4313017478 on OpenAlexaff
Dany Boulanger

Bibliographic record

VenueEstudos de Psicologia (Campinas) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicParental Involvement in Education
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsInvisibilityPhenomenonConstructiveRendering (computer graphics)Relation (database)EpistemologyPsychologySociologySocial psychologyProcess (computing)Computer sciencePhilosophyArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract: In this paper, I propose extending Tateo’s systemic cogenetic approach in relation with the dimensions of absence and invisibility. I illustrate my proposition in relation to the phenomenon of school-family-community interaction. I further develop my own theoretical work on how the interaction between school and family is constructed amidst tensions between presence versus absence, as well as visibility versus invisibility. This enables integrating the following dimensions in the systemic cogenetic approach: first, the process of making absence visible, invisible and present; and second, the process of rendering invisible the very process of constructing absence. I also delve into the constructive aspect of absence. I propose extending the systemic cogenetic approach in relation with the following aspects: (a) active absence (Goethe) as a way to make the invisible visible on the edge of the phenomenon; (b) the role of boundary in making visible the invisible; (c) boundary case (Non-Non-A) as a flexible designation (considering a phenomenon as A or non-A); and (d) circular and intransitive movement rendering visible the whole range of phenomena in irreversible time. I use the analysis of parents’ and teachers’ discourse as illustration of these theoretical propositions.

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)0.006
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0060.051
Scholarly communication0.0060.009
Open science0.0010.007
Research integrity0.0020.003
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 head0.049
GPT teacher head0.347
Teacher spread0.298 · 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 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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