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Record W4406055531 · doi:10.1177/02654075241312690

Talk about shared money: Account pooling is associated with financial communication

2025· article· en· W4406055531 on OpenAlexafffund
Johanna Peetz

Bibliographic record

VenueJournal of Social and Personal Relationships · 2025
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPoolingPsychologyFinanceSocial psychologyBusinessComputer science

Abstract

fetched live from OpenAlex

Couples who pool their financial resources tend to report more positive relationship outcomes. The present research examines whether more financial interdependence is linked to better and more frequent communication about financial decisions. Individuals who fully pool finances with their partner reported better financial communication quality and more frequent discussions about finances than individuals who partially pool finances or keep finances separate, even after controlling demographic differences and after controlling overall relationship satisfaction (Study 1). Financial account pooling was also strongly associated with greater likelihood to discuss hypothetical financial decisions with the partner (Study 2), and when experimentally assigned to focus on joint rather than separate financial accounts, this focus on pooled financial resources resulted in more willingness to discuss financial decisions with their partner (Study 3). Together, these studies show a novel aspect of how financial interdependence affect everyday interactions between partners: Couples who pool their financial resources talk more about money.

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)0.019
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 score0.007
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.043
GPT teacher head0.362
Teacher spread0.319 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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