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Record W2789191437 · doi:10.1177/0265407518756779

A labor of love? Emotion work in intimate relationships

2018· article· en· W2789191437 on OpenAlexafffund
Rebecca M. Horne, Matthew D. Johnson

Bibliographic record

VenueJournal of Social and Personal Relationships · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEmotional Labor in Professions
Canadian institutionsUniversity of AlbertaUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPsychologyAutonomyEmotion workSocial psychologyGermanDevelopmental psychologyJob satisfactionWork (physics)Latent class model

Abstract

fetched live from OpenAlex

Drawing on relational developmental systems and gender relations perspectives, this study analyzed data from 1,932 heterosexual couples from Waves 1 and 2 of the German Family Panel to answer three questions: (1) What are the longitudinal associations between male and female partners’ emotion work provision and relationship satisfaction? (2) Are there gender differences in associations between emotion work and relationship satisfaction? (3) Does autonomy moderate associations among these focal variables? An actor–partner interdependence model revealed emotion work was linked to heightened future relationship satisfaction, and female partners’ emotion work was the strongest predictor of both partners’ relationship satisfaction. Latent variable interactions demonstrated male partners’ emotion work was linked to female partners’ heightened relationship satisfaction only when men also reported high levels of autonomy. Emotion work may be a “labor of love” that builds future relationship satisfaction while under the differential “management” of autonomous self-representation and gender norms of affective care.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
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 head0.094
GPT teacher head0.358
Teacher spread0.265 · 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 designQualitative
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

Citations34
Published2018
Admission routes2
Has abstractyes

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