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Record W4281395849 · doi:10.31234/osf.io/e9nu6

Young Children Infer Psychological Ownership from Stewardship

2022· preprint· en· W4281395849 on OpenAlexafffundabout
Angelina Cleroux, Joann Peck, Ori Friedman

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsUniversity of Waterloo
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsStewardship (theology)FeelingAntecedent (behavioral psychology)Object (grammar)PsychologySocial psychologyBusinessPolitical science

Abstract

fetched live from OpenAlex

Although people of take care of their own possessions, they also engage in stewardship and take care of things they do not own. Here, we examine what young children infer when they observe stewardship behavior of an object. Through four experiments on predominantly middle-class Canadian children (total N = 350, 168 girls and 182 boys from a predominantly White and middle-class region), we find that children as young as four or five infer feelings of ownership from stewardship behaviors, and distinguish between psychological and legal ownership. They also understand that psychological and legal ownership are independent as one can exist without the other, and children as young as 3 may link stewardship with welfare concerns. We also suggest that while stewardship has been shown to be a consequence of psychological ownership, it is also likely to be an antecedent. As future stewards of our resources, young children’s understanding of the link between psychological ownership and stewardship links directly to sustainability concerns. We contribute theoretically both to the child development and the psychological ownership literatures.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.255

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.182
GPT teacher head0.335
Teacher spread0.153 · 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
Published2022
Admission routes3
Has abstractyes

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