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Record W2770780004 · doi:10.5539/ass.v13n12p103

Levels of Marital Satisfaction and its Relation to Some Variables on a Sample of Women in Amman City / Jordan

2017· article· en· W2770780004 on OpenAlexvenueno aff
Entisar Yousef Smadi

Bibliographic record

VenueAsian Social Science · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyMarital statusSample (material)DemographyClinical psychologyPopulationSociology

Abstract

fetched live from OpenAlex

The present study aimed to identify the level of marital satisfaction among a sample of women in Amman city / Jordan, and its relation to some variables, The sample included 165 women, it was randomly selected, the researcher designed a questionnaire that measures the level of marital satisfaction, which included 20 paragraphs, each paragraph measures one dimension related to marital satisfaction, The questionnaire was applied by the study members, The statistical analysis showed: 1- The level of marital satisfaction for all members of the study was medium level of marital satisfaction. 2- No statistically significant differences in marital satisfaction due to the variable number of years of marriage. 3- No statistically significant differences in marital satisfaction due to the variable number of children.4- No statistically significant differences in the levels of marital satisfaction between working and non-working women.5- There are statistically significant differences in marital satisfaction due to the variable educational level of women. 6- There are statistically significant differences in marital satisfaction due to the variable family income. This is a logical consequence of the nature of the study community.The study recommended providing preventive counseling services for young men and women before marriage, and provide counseling services for couples about mechanisms of effective marital interaction, in order to reduce the risk factors leading to marital failure.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.600
Threshold uncertainty score0.815

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.037
GPT teacher head0.322
Teacher spread0.284 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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