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Record W4386098052 · doi:10.31234/osf.io/k923p

Ownership and Value in Childhood

2023· preprint· en· W4386098052 on OpenAlexfundno aff
Madison L. Pesowski, Shaylene E. Nancekivell, Arber Tasimi, Ori Friedman

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicUrban Planning and Valuation
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsValue (mathematics)Affect (linguistics)FeelingControl (management)PsychologyBusinessPositive economicsSocial psychologyEconomicsManagement

Abstract

fetched live from OpenAlex

Ownership and value go together, and understanding both is imperative for children to know how to act in socially appropriate and advantageous ways. This paper reviews how children come to think about ownership and value. We first review how children consider history, labor, and control when inferring whether objects are owned and to whom they belong. We then review how children conceive of ownership rights and how they use ownership to anticipate other people's actions, feelings, and knowledge. With value, we first touch on children's attention to physical features and norms. We then discuss how ownership impacts children's valuations of objects, stemming both from children's own status as owners and from their knowledge of previous ownership. We also review how various kinds of distinctive histories affect children's valuations. Finally, we review children's understanding of how value depends on the market forces of supply and demand.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.011
Scholarly communication0.0050.005
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.058
GPT teacher head0.265
Teacher spread0.207 · 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 designTheoretical or conceptual
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
Published2023
Admission routes1
Has abstractyes

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