A Future “After Childhood”: Engaging the Anthropocene in Early Childhood Education
Bibliographic record
Abstract
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.,
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.049 |
| Scholarly communication | 0.013 | 0.018 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".