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Record W3014633770 · doi:10.1177/1948550619896671

Taking Stock of Reality: Biased Perceptions of the Costs of Romantic Partners’ Sacrifices

2020· article· en· W3014633770 on OpenAlexafffund
Mariko L. Visserman, Francesca Righetti, Amy Muise, Emily A. Impett, Samantha Joel, Paul A. M. Van Lange

Bibliographic record

VenueSocial Psychological and Personality Science · 2020
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsWestern UniversityYork UniversityUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSacrificePsychologySocial psychologyRomancePerceptionConversationCommunication

Abstract

fetched live from OpenAlex

When romantic partners sacrifice their own self-interest to benefit the relationship, the sacrificer or recipient may—for various reasons—be biased in how they perceive the costs that the sacrificer incurs. In Study 1, romantic couples ( N = 125) rated their own and their partner’s costs after a conversation about a sacrifice in the laboratory, followed by extensive experience sampling in their natural environment. In Study 2, a preregistered experiment, individuals ( N = 775) imagined a scenario in which they, their partner, or an unknown person sacrificed and rated the associated costs and benefits. Both studies demonstrated a consistent discrepancy between perceptions of own and partner sacrifice, driven primarily by people underestimating their own sacrifice costs and overestimating the benefits (Study 2). Results across studies showed that this underestimation bias helps people to feel better and feel more satisfied in the relationship when giving up their own goals and preferences for the relationship.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
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 head0.202
GPT teacher head0.496
Teacher spread0.294 · 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.

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

Citations21
Published2020
Admission routes2
Has abstractyes

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