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Record W4381678687 · doi:10.5539/jedp.v13n2p1

How Prospective Direct and Indirect Reciprocity Influence 4- to 6-Year-Old’s Sharing

2023· article· en· W4381678687 on OpenAlexvenueno aff
Yue Song, Yun Huang, Fenglin Zang

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2023
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsnot available
FundersGovernment of Jiangsu Province
KeywordsReciprocity (cultural anthropology)WitnessPsychologyNorm of reciprocitySocial psychologyDevelopmental psychologyPolitical scienceSocial capital

Abstract

fetched live from OpenAlex

Although an abundance of evidence support that preschoolers use reciprocity as a reply to others, lesser is known about how they use this strategy in initiating social interactions. Aiming to explore this question, the current study focused on two forms of prospective reciprocity, direct and indirect (downstream) reciprocity. Two studies were conducted in which the chance for prospective reciprocity was implicit (study 1) and explicit (study 2). Specifically, 4- to 6-year-olds were asked to share stickers with a non-shown recipient, a shown recipient, or a non-shown recipient while a witness was observing. In study 1, preschoolers did not know whether the shown recipient/witness would interact with them later. In study 2, they knew the shown recipient/witness would be asked to share with them subsequently. Results revealed that, despite the implicit/explicit chance of prospective reciprocity, preschoolers shared more in the prospective direct reciprocity condition than the control/prospective indirect downstream reciprocity conditions. In addition, comparing the two studies found no difference found between the implicit and explicit situations. Overall, these findings indicate that preschoolers have taken direct reciprocity, rather than indirect (downstream) reciprocity in guiding their initial sharing with others. Implications of these findings are further discussed.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.521

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)0.0000.000

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 head0.029
GPT teacher head0.335
Teacher spread0.306 · 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.

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
Published2023
Admission routes1
Has abstractyes

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