A Comparison of Housing Satisfaction in Rural and Urban Areas of Mafraq, Jordan
Bibliographic record
Abstract
Housing satisfaction is a multidimensional phenomenon that is affected by several factors.The aim of this study is to estimate the factors that affect housing satisfaction, including demographic factors such as household type, age, income, duration of residence, ownership of a house, and education.The physical features factors include the number of bedrooms and the quality of housing units.And the neighborhood facilities factors, including access to quality schools, quality of streets and roads, accessibility to public transportation, community and shopping facilities, and the physical environment.Examining how these factors affect housing satisfaction in urban and rural areas is the study's major goal.The questionnaire consists of three parts: the first part collects demographic characteristics; the second part measures the level of residents' satisfaction with the physical features; the third part measures the level of residents' satisfaction with the neighborhood environment.580 of the participants responded to the questionnaire.The participants of the study were from three communities: Mafarq City, Manshiyah, and Irhab, which administratively follow Mafraq governorate, Jordan.Manshiyah, and Irhab are considered rural communities.The results show that the level of housing satisfaction among residents in the city and the rural community is approximately the same, as most of the residents in the three communities share the same demographic characteristics, and they are satisfied with their houses, even though they are not satisfied with the neighborhood environment.The importance of this study comes from its results, since the neighborhood environment and facilities play a crucial role in raising the level of residents' satisfaction in their houses.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".