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Record W7060978084

Predictors of sexual satisfaction in Canadian heterosexual adults: An interdisciplinary approach

2004· dissertation· en· W7060978084 on OpenAlexaboutno aff

Bibliographic record

VenueThe Atrium (University of Guelph) · 2004
Typedissertation
Languageen
FieldEngineering
TopicSuperconducting Materials and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMultilevel modelSexual intercourseLogistic regressionHeterosexualityVariance (accounting)PopulationSample (material)Sexual behaviorRegression analysis
DOInot available

Abstract

fetched live from OpenAlex

This study examined predictors of sexual satisfaction in a representative sample of Canadian heterosexual adults ('N' = 1479) participating in a Compas national polling survey on relationships and sexuality. An interdisciplinary approach was used to bridge the existing gap between sociological and psychological research by incorporating both demographic and behavioural measures. Hierarchical logistic regression analysis determined the role of sociological variables (age, gender, marital status, educational attainment, religiosity, importance of religion, and region) and psychological variables (relationship problems, sexual self-disclosure, frequency of intercourse and sexual communication) in predicting participants' sexual satisfaction. The sociological variables accounted for 14% of the variance in sexual satisfaction, with the psychological variables predicting an additional 18% of the variance (32% for the full model). Frequency of intercourse was the strongest single predictor of sexual satisfaction. Results are discussed in terms of their implications for understanding sexual satisfaction in the Canadian population as a whole.

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)0.000
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 score0.814
Threshold uncertainty score0.752

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.012
GPT teacher head0.224
Teacher spread0.212 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

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