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Record W4400229466 · doi:10.1016/j.jecp.2024.105995

The impact of strategies on young children’s saving for the future

2024· article· en· W4400229466 on OpenAlexafffundabout
Ege Kamber, Madi K Maguire, Edyta K Tehrani, Tessa R. Mazachowsky, Caitlin E. V. Mahy

Bibliographic record

VenueJournal of Experimental Child Psychology · 2024
Typearticle
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsBrock University
FundersOntario Ministry of Economic Development, Job Creation and TradeOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and Science
KeywordsPsychologyControl (management)Tracking (education)Perspective (graphical)Developmental psychologyEarly childhoodEarly childhood educationCovariateEconomicsPedagogy

Abstract

fetched live from OpenAlex

The ability to save resources for future use, or saving, begins to emerge around 3 years of age, but children show low rates of saving during the preschool years. Thus, several strategies have been used to improve preschoolers' saving, such as providing a prompt, budgeting, increasing psychological distance, and simulating the future. The current study investigated (a) the development of saving in early childhood, (b) the impact of several saving strategies on children's saving (i.e., budgeting, tracking expenses, and psychological distance), and (c) whether the effectiveness of the strategies changed with age. Here, 3- to 5-year-old Canadian children (N = 254) completed the Saving Board Game, and their parents completed the saving subscale of the Children's Future Thinking Questionnaire. In the Saving Board Game, children were randomly assigned to one of the five strategies: (a) control, (b) budgeting, (c) tracking, (d) adult perspective, or (e) child perspective. An analysis of covariance with age, strategy, and response option order (as a covariate) showed a main effect of age, with 5-year-olds saving more than 3-year-olds. There was no effect of strategy or an interaction between strategy and age on children's token saving. Parent-reported child saving was positively correlated with children's Saving Board Game performance only in the control condition. We consider why these strategies failed to increase children's saving.

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.731
Threshold uncertainty score0.464

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.072
GPT teacher head0.491
Teacher spread0.419 · 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

Citations4
Published2024
Admission routes3
Has abstractyes

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