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Record W2486322515 · doi:10.1075/ceb.6.10car

Reaching, requesting and reflecting

2012· book-chapter· en· W2486322515 on OpenAlexaff
Jeremy I. M. Carpendale, Charlie Lewis

Bibliographic record

VenueConsciousness & emotion book series · 2012
Typebook-chapter
Languageen
FieldSocial Sciences
TopicEducational and Social Studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPsychologyHistory

Abstract

fetched live from OpenAlex

From many contemporary theoretical perspectives, the body and emotions play little role in the development of thinking and consciousness. If emotions are given any part it is in biasing thinking, rather then contributing to cognitive development. This volume, in contrast, presents alternatives to that position. From our perspective, embodied engagement with others – necessarily involving emotions – has a role in structuring the interactional conditions in which the development of thinking occurs. Just the body and emotions, however, are insufficient; the mythical baby isolated on a desert island would have a body and emotions (or at least the potential for their further development), but would not go on to develop human forms of thinking. What is needed is a shared history of routine patterns of interpersonal engagement. The body and emotions are necessary for setting up these forms of interaction and routines in which communication can emerge and then thinking and consciousness. In this sense, the development of human forms of thinking requires a social environment. We draw from Mead the point that self-awareness arises from interacting with others, and thus, self-consciousness is inherently social (Farr 1980; Mead 1909, 1910a, 1910b, 1922, 1934; Morss 1985). Keywords: Infant communication; gestures; social cognition; meaning; G.H. Mead

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)0.001
metaresearch head score (Gemma)0.009
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.027
Threshold uncertainty score0.092

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.010
Scholarly communication0.0070.011
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0270.014

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 head0.069
GPT teacher head0.338
Teacher spread0.269 · 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
GenreOther

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

Citations5
Published2012
Admission routes1
Has abstractyes

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