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Record W3047487955 · doi:10.1177/0146167220946195

Secrets, Psychological Health, and the Fear of Discovery

2020· article· en· W3047487955 on OpenAlexafffund
Christopher G. Davis, Hannah Brazeau, Elisabeth Bailin Xie, Kathleen Burke McKee

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2020
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsCarleton University
FundersCarleton University
KeywordsPsychologyAffect (linguistics)Social psychologyRomanceMultilevel modelLife satisfactionDevelopmental psychologyPsychoanalysisCommunication

Abstract

fetched live from OpenAlex

Keeping secrets from one’s partner has been associated with lower well-being and relationship satisfaction. Previous research has suggested that individual differences in self-concealment account for these effects. However, we propose that the fear of discovery (FoD)—defined as the fear that one’s secret may be revealed by means other than deliberate disclosure—predicts the extent to which secrets affect well-being beyond the effects attributable to individual differences. Both a cross-sectional and a longitudinal survey (combined N = 471; 54.4% female; M age = 39.5) of adults in romantic relationships confirmed that FoD predicted greater preoccupation with the secret, more negative affect, and less relationship satisfaction and commitment beyond that of self-concealment. Multilevel modeling in Study 2 indicated that changes in FoD predicted changes in preoccupation over time. The data are consistent with the notion that FoD promotes greater preoccupation, greater negative affect, and lower levels of relationship well-being.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.716
Threshold uncertainty score0.597

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.062
GPT teacher head0.421
Teacher spread0.359 · 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 teacher head, 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

Citations24
Published2020
Admission routes2
Has abstractyes

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