MétaCan
Menu
Back to cohort
Record W4414690528 · doi:10.1111/pere.70032

When Love and Money Collide: The Role of Financially Focused Self‐Concept in Relationships

2025· article· en· W4414690528 on OpenAlexafffund
Johanna Peetz, Michael J. A. Wohl, Nassim Tabri

Bibliographic record

VenuePersonal Relationships · 2025
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPerceptionRomanceSample (material)Harmony (color)Financial marketExploratory researchFinancial transactionPositive relationship

Abstract

fetched live from OpenAlex

ABSTRACT This research examined whether people's own and their partner's financially focused self‐concept are associated with relationship satisfaction in a sample of UK couples ( N = 388 participants). Results showed that financial harmony in a romantic relationship is influenced not only by an individual's own financial focus but also by their partner's financial focus. Contrary to expectations, however, the degree to which financial resources were integrated (i.e., pooled) between partners did not moderate this link. Exploratory analyses tested financial stress, financial harmony, and financial infidelity as possible mediators of the link between people's own and their partner's financially focused self‐concept and relationship outcomes. When perceiving the partner as overly focused on financial success, they were more likely to endorse financial infidelity and reported lower financial harmony, which in turn was associated with poorer relationship outcomes. Indeed, the perception of excessive financial focus appeared to be more detrimental to the relationship than the partner's actual financial focus. These findings highlight the importance of assessing the financial attitudes of both partners as well as their perception of each other's financial attitudes in shaping romantic relationship outcomes.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.245
Threshold uncertainty score0.601

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.025
GPT teacher head0.321
Teacher spread0.296 · 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

Citations1
Published2025
Admission routes2
Has abstractyes

Explore more

Same venuePersonal RelationshipsSame topicAttachment and Relationship DynamicsFrench-language works237,207