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Record W4392914251 · doi:10.1080/09575146.2024.2329595

Ongoing attachments with stuffed toys: conceptualizing childhood and teaching through transitional objects

2024· article· en· W4392914251 on OpenAlexafffund
Sandra Chang‐Kredl, Lisa Farley, Julie C. Garlen, Debbie Sonu

Bibliographic record

VenueEarly Years Journal of International Research and Development · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsCarleton UniversityYork UniversityConcordia University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

In this article, we highlight how adults remain emotionally involved with transitional objects, such as stuffed animals, carried over from their childhoods. Drawing on focus groups involving undergraduate students enrolled in teacher education and childhood studies programs, we found that the participants’ reflections of their stuffed animals opened onto layered meanings: 1) tactile experiences of materiality and sensation; 2) personal memories of innocence and paternal protection; and 3) conceptualizations of uncertainty and anxiety in adulthood. While we found that stuffed animals can be important access points to underrepresented feelings of vulnerability in adulthood, we also noted that these transitional objects can be used to entrench normative notions of teaching, development, and childhood. We suggest that transitional objects can be resources in fields devoted to the well-being and growth of children, especially as they help prospective teachers work through the ambivalences and defenses that accompany the work of education and care.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.007
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0050.027
Scholarly communication0.0070.010
Open science0.0020.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.084
GPT teacher head0.423
Teacher spread0.339 · 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

Citations6
Published2024
Admission routes2
Has abstractyes

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