Headship rate projections for housing demand in Johor, \nMalaysia
Bibliographic record
Abstract
Household formation trend is closely linked with the numbers of population. \nMeanwhile, the formation of households is largely influenced by the composition of the adult \npopulation that are measured by headship rate. This paper attempts to project headship rate \nwhich acts as a main predictor in determine potential housing demands. Population and \nHousing Census data from year 2000 and 2010 has been used in this projection headship rate \nfor Johor state. Modified two-point exponential method was applied to determine the headship \nrate. All the data was categorized into five years interval for the ages between 15 to 80+ years \nold. Results indicate that the projected headship rates for age 15-19 and 20-24 are significantly \ndecreased. However for the age’s groups 40-44, 50-54, 55-59 75-79 and 80+ years old, the \nprojected headship rate increased until year 2020. This demonstrates, the decreasing ability of \nyoung people under 25 years to become homeownership as compared to people from the age \ngroups of 40 years and above. The findings of this study could be used as a basis for the \ngovernment to identify numbers of potential housing demand in Johor.
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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) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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".