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Record W2036372285 · doi:10.2466/pr0.104.2.379-387

Dimensionality and Reliability of a Modified Version of Norton's 1983 Quality Marriage Index among Expectant and New Canadian Mothers

2009· article· en· W2036372285 on OpenAlexaffabout
R. Roudi Nazarinia, Walter R. Schumm, James White

Bibliographic record

VenuePsychological Reports · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPsychologyIndex (typography)Reliability (semiconductor)Curse of dimensionalityQuality (philosophy)Dimension (graph theory)StatisticsComputer scienceMathematicsPower (physics)

Abstract

fetched live from OpenAlex

A slightly modified version of Norton's 1983 Quality Marriage Index was administered to 61 expectant mothers prior to giving birth and within 3 mo. after giving birth. Mothers' ages ranged from 19 to 43 years (M = 30, SD = 5.01) and their partners' ages ranged from 21 to 48 years (M = 32, SD = 6.02). Mothers were presented an opportunity to participate in this study during prenatal classes held at hospital and community health centers. The only requirement for participation was that the mother be residing with her child's father for the duration of the study. The six items of the modified index showed high internal consistency (alpha > .90) and substantial test-retest reliability with a Pearson zero-order correlation of .65 across the two administrations. Maximum likelihood factor analysis indicated moderate support for unidimensional factor structure for the modified index, but removing one item from the pre- and postnatal administration improved the factor structure. In the first administration, the last item (overall current satisfaction with partner) fit poorly with the factor structure, while at the second administration, the second item (our relationship is very stable) fit poorly. Possible implications of the results are discussed.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.149
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.044
GPT teacher head0.343
Teacher spread0.299 · 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

Citations12
Published2009
Admission routes2
Has abstractyes

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