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Record W4310603557 · doi:10.1177/20551029221142465

Men, relationships and partner-initiated break-ups: A narrative analysis

2022· article· en· W4310603557 on OpenAlexaff
John L. Oliffe, Mary T. Kelly, Gabriela Gonzalez Montaner, David Kealy, Zac E. Seidler, John S. Ogrodniczuk, Paul Sharp, Simon Rice

Bibliographic record

VenueHealth Psychology Open · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicGender Roles and Identity Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNarrativeIntrospectionNarrative inquiryPsychologyAgency (philosophy)Psychological interventionSocial psychologyDemiseMental healthAccountabilityGeneral partnershipPower (physics)Developmental psychologyPsychotherapistSociologyPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

For men, significant risks associated with partner-initiated break-ups include domestic violence, mental health challenges and difficultly with life transition. This narrative analysis study shares three storylines drawn from interviews with 25 men who experienced a partner-initiated break-up. Ill equipped to stay or to initiate leaving narratives positioned participants as conflict averse, lacking agency and withdrawing emotionally from the partnership and its demise. Victims of circumstance narratives included men who engaged in cyclic arguments and ongoing power struggles with partners, a pattern that often amplified conflict after the break-up. Transitioning these two impasse narratives were some participants whose Accountability and growth storylines highlighted their introspective self-work, aided by resources including professional help to deconstruct, understand, and adjust their behaviours. Making connections to masculinities theory, these findings suggest that tailored interventions, including narrative therapy, might usefully interrupt impasse narratives to aid men's development and healthful transitions through partner-initiated break-ups.

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)0.004
metaresearch head score (Gemma)0.007
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.002
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.302
GPT teacher head0.516
Teacher spread0.214 · 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

Citations5
Published2022
Admission routes1
Has abstractyes

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