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Record W571959045 · doi:10.2174/1874350101508010071

Intimacy, Loneliness & Infidelity

2015· article· en· W571959045 on OpenAlexaff
Ami Rokach, Gwenaëlle Philibert-Lignières

Bibliographic record

VenueThe Open Psychology Journal · 2015
Typearticle
Languageen
FieldPsychology
TopicEvolutionary Psychology and Human Behavior
Canadian institutionsYork University
Fundersnot available
KeywordsLonelinessPsychologyBetrayalSocial psychologyConstruct (python library)Interpersonal communicationDistressInterpersonal relationshipDevelopmental psychologyClinical psychology

Abstract

fetched live from OpenAlex

This article explores the experience of loneliness in intimacy, with a special focus on infidelity. First, the notion of intimacy and love are examined and related to the concept of loneliness. To be in love is often thought to exclude being lonely but research shows otherwise.’ Loneliness is exacerbated when intimacy is shattered by interpersonal events like infidelity. A review of recent literature regarding infidelity is presented. The concepts of depression, social support, self-esteem, and betrayal as a result of infidelity are examined and linked to loneliness. Also included, is a small discussion regarding the psychological distress and loneliness of the adulterer, before and after the revelation of infidelity. It is further asserted that loneliness is a two-way construct when speaking of infidelity; not only is it a salient product of infidelity, but also a strong predictor of its occurrence.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.277
GPT teacher head0.505
Teacher spread0.228 · 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

Citations28
Published2015
Admission routes1
Has abstractyes

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