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Record W2041059902 · doi:10.1177/0265407501184002

Deception in Romantic Relationships: Subjective Estimates of Success at Deceiving and Attitudes toward Deception

2001· article· en· W2041059902 on OpenAlexaff
Susan D. Boon, Beverly A. McLeod

Bibliographic record

VenueJournal of Social and Personal Relationships · 2001
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsRoyal College of Physicians and Surgeons of CanadaMount Royal UniversityUniversity of Calgary
Fundersnot available
KeywordsDeceptionHonestyPsychologyDishonestyLyingRomanceSocial psychologyPerceptionPsychoanalysisMedicine

Abstract

fetched live from OpenAlex

Participants (N = 97) completed a questionnaire about deceptive communication in romantic relationships. Responses indicated that people generally believe that they are fairly successful in their efforts to deceive their partners and, moreover, that they believe they are more successful in deceiving their partners than their partners are at deceiving them. Results also suggest that attitudes toward dishonesty in romantic relationships are neither as simple nor straightforward as the costs associated with discovery might lead one to expect. In addition, participants' beliefs about the importance of honesty in romantic relationships and their perceptions regarding their own and their partner's success at deceiving one another predicted their use of certain modes of deception (i.e., falsification), as well as their responses to suspected deception (both how they responded when they suspected their partner may be lying and how they reacted to a partner's suspicions that they had been dishonest).

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)0.005
metaresearch head score (Gemma)0.030
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 score0.005
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.030
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.099
GPT teacher head0.363
Teacher spread0.264 · 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

Citations40
Published2001
Admission routes1
Has abstractyes

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