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Record W2908406410 · doi:10.5539/ies.v12n1p80

Students’ Attitudes at Amman Arab University towards the Pre-Marital Medical Examination and Its Role in Reducing Disability from Their Point of View

2018· article· en· W2908406410 on OpenAlexvenueno aff
Ahmad Khazaleh, Tayel Abdel Hafez Hwaidi, Mo’en Salman Alnasraween, Heyam Al-Taj

Bibliographic record

VenueInternational Education Studies · 2018
Typearticle
Languageen
FieldMedicine
TopicHealthcare Systems and Public Health
Canadian institutionsnot available
Fundersnot available
KeywordsMarital statusPsychologyMedical educationSample (material)Descriptive researchMedicineSociologyDemographySocial science

Abstract

fetched live from OpenAlex

The purpose of this study is to identify the attitudes of the students of Amman Arab University toward pre-marital medical examination; it also aims to identify the role of premarital examination in reducing the appearance of disabilities. This study used the descriptive method; the sample of the study consisted of 200 undergraduate and master’s students at Amman Arab University from the different faculties and academic years for the year (2017-2018). The researchers used a questionnaire; it consisted in its final form of 24 items. The results of the study showed that the mean of the total score of the role of the medical examination from the point of view of young people came to a high level; results also showed that there are no differences due to the gender of the student or the type of college.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.070
GPT teacher head0.420
Teacher spread0.350 · 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

Citations5
Published2018
Admission routes1
Has abstractyes

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