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Record W2096464146 · doi:10.1111/jopy.12222

Longing for Ex‐Partners out of Fear of Being Single

2015· article· en· W2096464146 on OpenAlexafffund
Stephanie S. Spielmann, Geoff MacDonald, Samantha Joel, Emily A. Impett

Bibliographic record

VenueJournal of Personality · 2015
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsBreakupPsychologyRomanceAnxietyDevelopmental psychologyFear of fallingConstruct (python library)Clinical psychologySocial psychologyPoison controlPsychoanalysisSuicide preventionPsychiatryMedicineMedical emergency

Abstract

fetched live from OpenAlex

Abstract This research investigated whether people who fear being single have a more difficult time letting go of ex‐partners following a romantic breakup. Data were collected in a cross‐sectional study ( N = 209, 64% women, M age = 30 years old) as well as a 1‐month daily experience study of individuals who just went through a romantic breakup ( N = 117, 44% women, M age = 27 years old). Findings from both studies revealed that those with stronger fear of being single (Spielmann et al., 2013) reported greater longing for their ex‐partners. Pre‐ to post‐breakup analyses revealed that fear of being single increased after a breakup, regardless of who initiated the breakup. Within‐day analyses revealed that longing for an ex‐partner and attempts to renew the relationship were greater on days with stronger fear of being single. Lagged‐day analyses provided support for the conclusion that fear of being single increased longing and renewal attempts over time, but longing and renewal attempts did not influence fear of being single. These findings suggest that fear of being single is a particularly useful construct for understanding the romantic detachment process.

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)0.002
metaresearch head score (Gemma)0.008
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 score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.143
GPT teacher head0.470
Teacher spread0.327 · 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

Citations70
Published2015
Admission routes2
Has abstractyes

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