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Record W3035219013 · doi:10.1080/01596306.2020.1779448

Introduction to Symposium: childhood studies in the Anthropocene

2020· article· en· W3035219013 on OpenAlexaff
Peter Kraftl, Affrica Taylor, Veronica Pacini-Ketchabaw

Bibliographic record

VenueDiscourse Studies in the Cultural Politics of Education · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsWestern University
Fundersnot available
KeywordsAnthropoceneScholarshipEnvironmental ethicsHistorySociologyPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Childhood studies scholars have increasingly sought to examine the complex entanglements of children's lives with nonhuman materials, animals, plants and earthly processes. Doing so has enabled new insights into children's relationships with global challenges such as climate change. Now, researchers from many disciplines are reflecting critically upon whether such challenges can be obviously ascribed to human activity, suggesting that we are entering a new (geological) epoch: the Anthropocene. The present collection of papers offers a range of empirically-informed, critical and theoretical analyses of the (possible) relationships between children and the Anthropocene. This paper frames the key debates covered in the symposium, introducing recent scholarship in childhood studies and opening out critical reflections on the term ‘Anthropocene’. It also provides an introduction to the papers making up the symposium.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.060
Threshold uncertainty score0.201

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0050.003
Scholarly communication0.0090.006
Open science0.0020.006
Research integrity0.0080.011
Insufficient payload (model declined to judge)0.0600.013

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 head0.037
GPT teacher head0.386
Teacher spread0.349 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations24
Published2020
Admission routes1
Has abstractyes

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