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Record W4224056517 · doi:10.1080/14681366.2022.2063930

The critical work of memory and the nostalgic return of innocence: how emergent teachers represent childhood

2022· article· en· W4224056517 on OpenAlexafffundabout
Lisa Farley, Julie C. Garlen, Sandra Chang‐Kredl, Debbie Sonu

Bibliographic record

VenuePedagogy Culture and Society · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicChildren's Rights and Participation
Canadian institutionsConcordia UniversityCarleton UniversityYork University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsInnocenceSociologyIdeal (ethics)AestheticsPsychologyPsychoanalysisEpistemologyArtPhilosophy

Abstract

fetched live from OpenAlex

This article examines how participants enrolled in teacher education and childhood studies courses represented their understandings of childhood through a selection of artefacts discussed in focus groups at four sites: Montréal, New York City, Ottawa, and Toronto. To situate our inquiry, we theorise nostalgia in relationship to the construction of childhood innocence, with a focus on children’s everyday objects and playthings in upholding this ideal. We further trace the construction of innocence to discourses of social exclusion and defences against difficulty. While participants used their artefacts to represent personal memories and social contexts that disrupted an idealised category of childhood, they also returned to a nostalgic trope of innocence, which was particularly pronounced in their understandings of childhood under COVID-19. We advocate for the creation of time and space for prospective and practicing teachers to mourn the idealisation of innocence and to examine the unequal conditions of vulnerability that both children and teachers live.

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)0.007
metaresearch head score (Gemma)0.013
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 score0.048
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0140.082
Scholarly communication0.0110.009
Open science0.0020.010
Research integrity0.0020.004
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 head0.020
GPT teacher head0.329
Teacher spread0.309 · 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

Citations9
Published2022
Admission routes3
Has abstractyes

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