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Record W4234611154 · doi:10.22215/etd/2015-11175

Preschoolers' Development of Intent-Based Moral Judgement and the Role of Theory of Mind

2015· dissertation· en· W4234611154 on OpenAlexaff
Katherine Andrews

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsCarleton University
Fundersnot available
KeywordsJudgementCharacter (mathematics)PsychologyTheory of mindPunishment (psychology)Social psychologyMoral characterIdentification (biology)Relation (database)Moral developmentTask (project management)Dual (grammatical number)Developmental psychologyEpistemologyLinguisticsCognitionPhilosophyComputer scienceMathematics

Abstract

fetched live from OpenAlex

The current study examined 4-and 5-year-old children's ability to use intention information in their moral judgements of story characters with identical, neutral intentions that produced different outcomes (one neutral and one negative).Children were presented with two story types: stories in which two characters are included, and stories in which only one character is presented.It was hypothesized that children would show more mature moral reasoning when they were given the chance to directly compare the characters, especially their matched intentions, when they are presented within a single story, compared to across stories.However, results revealed that children's moral ratings were less mature when presented with dual-character stories compared to singlecharacter stories.On the other hand, children's assignment of punishment and identification of the characters' intentions did not differ depending on the story type.Performance on the task was also examined in relation to false belief understanding.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.018
GPT teacher head0.281
Teacher spread0.263 · 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 designObservational
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
Published2015
Admission routes1
Has abstractyes

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