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Record W4406311937 · doi:10.7202/1115436ar

Textiles and the Creative Possibilities of Assemblage Thinking in Early Childhood: A Narrative Look

2023· article· en· W4406311937 on OpenAlexaff
Catherine-Laura Dunnington

Bibliographic record

VenueInternational Journal for Talent Development and Creativity · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAssemblage (archaeology)NarrativeAestheticsEarly childhoodVisual artsSociologyPsychologyArtHistoryLiteratureDevelopmental psychologyArchaeology

Abstract

fetched live from OpenAlex

As textiles continue to feature heavily in discussions of sustainability, and young students continue to be positioned as saviors of the planet, this paper joins the call for assemblage thinking in early years research that decenters humans and foregrounds relationships. What follows is a subset of a larger study, where one preschool classroom engaged with textile themed provocations, and I had the honor of listening deeply to the children. This work borrows from sociomaterialism and artistic listening to consider what themes emerged when I considered child/textile as entangled in meaning making in one senior preschool classroom. I highlight ways in which the themes of connect, know, and perceive all surface in one richly detailed narrative of children making meaning with textiles. Finally, I offer a way in which research can support this kind of assemblage thinking in the classroom, by looking to relationships between themes and how we might represent those relationships in more nuanced, illustrative ways.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0090.034
Scholarly communication0.0090.009
Open science0.0010.008
Research integrity0.0020.004
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 head0.027
GPT teacher head0.290
Teacher spread0.262 · 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
Published2023
Admission routes1
Has abstractyes

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