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Record W4380362172 · doi:10.18357/jcs482202321253

A Future “After Childhood”: Engaging the Anthropocene in Early Childhood Education

2023· article· en· W4380362172 on OpenAlexaffvenue
Paolo Russumanno

Bibliographic record

VenueJournal of Childhood Studies · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicPosthumanist Ethics and Activism
Canadian institutionsWestern University
Fundersnot available
KeywordsAnthropoceneEarly childhoodEarly childhood educationDevelopmental psychologyPsychologyEnvironmental ethicsPhilosophy

Abstract

fetched live from OpenAlex

s work After Childhood: Re-thinking Environment, Materiality, and Media in Children's Lives (Routledge, 2020) demands a strenuous exercise in reading, thinking, and imagining new ways of seeing and becoming within the field of childhood studies.Broadly speaking, this is a methodological experiment that mostly uses the theoretical positioning of new materialist and posthumanist thinking to unlock the potential for further interdisciplinary research.In this pursuit, Kraftl relentlessly breaks open scholastic silos, humanist languages, and widely agreedupon ways of knowing to present a carefully curated hodgepodge of disciplinary endeavours that reimagine the child and the world.At its core, this is the motivation for thinking with after childhood.As a human geographer and childhood studies scholar who embraces the spirit of new materialism, Kraftl has a unique disposition that encourages him to experiment with different methods across multiple disciplines.His entire work is a sensibly frenetic, gradual, and meandering procession in, out, and across a variety of scales.In each chapter, Kraftl pulls the reader into an unravelling exploration of intellectual curiosity, cautiously guiding the reader while simultaneously hurrying them to keep pace.Kraftl acts as a metaphorical tour guide in foreign lands, introducing wide-eyed child scholars to traditionally taboo disciplines and an emerging culture of embraced unknowns and becomings (Haraway, 2008).This tour of the unknown is necessary, not just for Kraftl's work, but for understanding and embracing the very difficult work of decentering oneself to embrace, welcome, and explore the entanglements, relations, and affects that emerge when we actively and insecurely position ourselves within the common worlds to think and become alongside the more-than-human (Kraftl et al.,

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)0.002
metaresearch head score (Gemma)0.001
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 score0.840
Threshold uncertainty score0.895

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.022
GPT teacher head0.339
Teacher spread0.317 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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