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The Development of Moral Self-Presentation

2020· reference-entry· en· W3011905362 on OpenAlexaff
Robin Banerjee, Gail D. Heyman, Kang Lee

Bibliographic record

Venuenot available
Typereference-entry
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyPresentation (obstetrics)Presentational and representational actingSocial psychologyDeceptionMoral developmentProsocial behaviorSocial cognitive theory of moralityMoral disengagementContext (archaeology)Self-disclosureAesthetics

Abstract

fetched live from OpenAlex

Children come to recognize that the impressions one makes on other people can be controlled and managed. In this chapter, the authors situate the development of such “self-presentation” in the moral context, with attention to a range of relevant social, cultural, cognitive, motivational, and emotional processes. Children’s appreciation of self-presentational tactics such as self-promotion, modesty, and ingratiation is reviewed before turning specifically to the factors involved in deception and truth-telling. The authors analyze the emergence of children’s self-presentational competencies in shaping both their own individual reputations and the reputations of the social groups with which they identify, especially in contexts where moral and social-conventional rules have been transgressed. Key goals for future research that illuminates the nature and implications of children’s moral self-presentation are identified.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.122
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.050
GPT teacher head0.327
Teacher spread0.277 · 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.

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

Citations8
Published2020
Admission routes1
Has abstractyes

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