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Record W2614325462 · doi:10.1590/1413-82712017220111

The Experiences in Close Relationships - Relationship Structures Questionnaire (ECR-RS): validity evidence and reliability

2017· article· en· W2614325462 on OpenAlexaff
Gláucia Mitsuko Ataka da Rocha, Evandro Morais Peixoto, Tatiana de Cássia Nakano, Ivonise Fernandes da Motta, Daniela Wiethaeuper

Bibliographic record

VenuePsico-USF · 2017
Typearticle
Languageen
FieldPsychology
TopicAttachment and Relationship Dynamics
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsRasch modelPsychologyCategorical variableReliability (semiconductor)Internal consistencyExploratory factor analysisScale (ratio)Developmental psychologyPsychometricsClinical psychologyStatisticsMathematics

Abstract

fetched live from OpenAlex

Abstract The ECR-RS assesses attachment in close relationships: father, mother, romantic partners and friends. Each relationship is assessed by a scale that theoretically comprises two factors: anxious and avoidant attachment. The main goals of this research was to estimate the first evidences of internal structure validity and reliability of the ECR-RS Brazilian version, and describe the item parameters and participants’ characteristics. The sample comprised 251 participants (mean age: 28.21 ± 10.29; 81.95% women). The categorical Exploratory Factor Analysis revealed two-dimensional structure of the scales, as theoretically hypothesized, with desirable internal consistency indexes. The Rasch-Masters Partial Credit Mode indicated that the instrument items have a level of difficulty close to the mean and suitable adjustments indexes (Infit/Outfit), and summarized description of participants’ theta levels. The results suggest that the instrument is an appropriate measure of attachment in adults.

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)0.004
metaresearch head score (Gemma)0.010
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 score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.118
GPT teacher head0.433
Teacher spread0.316 · 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

Citations26
Published2017
Admission routes1
Has abstractyes

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Same venuePsico-USFSame topicAttachment and Relationship DynamicsFrench-language works237,207