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Record W3198833027

Implicit Partner Evaluations: How They Form and Affect Close Relationships

2021· article· en· W3198833027 on OpenAlexaff
Ruddy Faure

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2021
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsCentre for Movement Disorders
Fundersnot available
KeywordsAffect (linguistics)Social psychologyPsychologyCommunication
DOInot available

Abstract

fetched live from OpenAlex

For decades, research on couples has attempted to understand the source of relationship decay by explicitly asking people how they evaluate their relationships. Ironically, however, relationship science also indicates that people seem largely indisposed to acknowledge some aspects of their relationships in self-report questionnaires, particularly when those are undesirable. To circumvent these limitations, a growing body of work has started to employ more indirect measurement tools (the so-called ‘implicit measures’) to capture people’s spontaneous evaluative associations, or gut-feeling reactions, toward their partner: their implicit partner evaluations. Recent evidence suggests that implicit partner evaluations, as assessed by implicit measures, differ quite sharply from self-reported explicit evaluations and predict later relationship quality and stability, even when explicit evaluations do not. To date, however, little is known about the sources of implicit partner evaluations and the reasons why they have such powerful predictive power. The present dissertation contributes to this growing field of research in many ways by examining how implicit partner evaluations form and affect close relationships in everyday life. First, using a combination of longitudinal and observational methods, Chapter 2 provides evidence that, compared to their explicit counterparts, implicit partner evaluations remain more stable over time, are more resistant to day-to-day relationship experiences, and update gradually as relationship experiences accumulate in time. Second, Chapters 3 and 4 capitalize on diary and experimental designs to show that one of the reasons why implicit partner implicit partner evaluations have important implications for relationship maintenance is because, under specific yet prevalent conditions (i.e., when opportunities to deliberate are limited), they determine daily behaviors that are critical for long-term relational well-being, such as nonverbal communication in problem-solving conversations and forgiveness toward the partner’s offense. Third, drawing on a large dyadic sample of newlyweds, Chapter 5 further extends these findings by showing that having ambivalent implicit partner evaluations can also affect relationship functioning over time by motivating spouses to make behavioral efforts that may improve their marital problems. Last, Chapter 6 describes how studying implicit evaluations in close relationship contexts can also invigorate basic implicit social cognition research on how attitudes change and affect behavior in the real world, and inform interventions for society. Taken together, the findings from the present dissertation provide novel insights about the key role of implicit partner evaluations in relational contexts, and further illustrate the scientific and practical value of integrating research in relationship science and implicit social cognition.

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)0.003
metaresearch head score (Gemma)0.018
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 score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.059
GPT teacher head0.394
Teacher spread0.336 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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