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PLAYING WITH DOLLS: (RE)STORYING GENDERED CARING PEDAGOGIES

2014· article· en· W2107211348 on OpenAlexaffvenue
B. Denise Hodgins

Bibliographic record

VenueInternational Journal of Child Youth and Family Studies · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsSituatedIndividualismSociologyEarly childhoodGender studiesDominance (genetics)Early childhood educationPedagogyPsychologyDevelopmental psychologyPolitical science

Abstract

fetched live from OpenAlex

Based on material discussed more fully in Chapter 4 of the author’s Ph.D. dissertation (Hodgins, 2014), this article shares ordinary classroom stories of child-doll encounters that occurred during a collaborative research study that explored how children, educators, and things emerge as gendered caring subjects within early childhood practices. The historical and current dominance of dolls in early childhood practices and their links to gender and care make dolls such a significant material to think-with. Following Donna Haraway, this article works to unstick early childhood pedagogies from individualist and child-centred pedagogies, and rethink the apolitical and developmental logics that underpin “doll early childhood pedagogies”. Through thinking-with dolls, new trajectories for dolls in the classroom are created. These trajectories highlight children’s relations with/in the world situated within practices in, near, and far from the classroom, and the becoming of gendered caring subjects as a materialsemiotic entanglement rather than a performed or predestined linear development. Implications for caring pedagogies are considered, including the necessity for making visible the interconnectedness of gender and care, tracing how (particular) practices come to matter, and responding within the complexity of knotted webs of relationality.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.313
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.100
GPT teacher head0.354
Teacher spread0.254 · 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 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

Citations14
Published2014
Admission routes2
Has abstractyes

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