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Record W4401035029 · doi:10.1027/2698-1866/a000078

Validation of the German Intimacy Scale

2024· article· en· W4401035029 on OpenAlexaff
Sonja Weilenmann, Alexander von Luckner, Charlotte Huber, Carolyn Birnie‐Porter, Monique C. Pfaltz, Billy Jansson

Bibliographic record

VenuePsychological Test Adaptation and Development · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsSaint Mary's University
Fundersnot available
KeywordsGermanScale (ratio)PsychologyComputer scienceGeographyArchaeologyCartography

Abstract

fetched live from OpenAlex

Abstract: The intimacy questionnaire by Birnie (2009 ; Birnie-Porter & Lydon, 2013 ) is a promising measure of relationship intimacy due to its strong theoretical background, the inclusion of lay conceptions and the differentiation of emotional and sexual intimacy. This study aimed to validate our German translation of Birnie’s questionnaire, which we labeled Intimacy Scale (IS). In two independent samples (379 and 203 individuals), confirmatory factor analyses showed best support for a bifactor S-1 model, with a strong general intimacy factor and a small specific factor, capturing unique portions of the variance related to sexual intimacy. The general intimacy factor correlated very highly and to the point of redundancy with relationship quality. Taken together, the IS may be useful as measure of relationship quality with a general (intimacy) factor. Future research is needed to improve the factorial structure of the scale.

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)0.007
metaresearch head score (Gemma)0.013
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: Methods · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.080
GPT teacher head0.368
Teacher spread0.288 · 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
GenreMethods

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

Citations1
Published2024
Admission routes1
Has abstractyes

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