Tertiary students’ housing priorities: Finding home away from home
Bibliographic record
Abstract
Globally, 5 million students annually leave both high school and their homes for the first time in pursuit of a higher education, while some others may be transiting to a new country in search of an international education. If tertiary students are unable to access suitable accommodation, this could have several implications. First is the significant role of housing on one’s health, wellbeing, and quality of life as this can be an additional cause for stress and worry. Second, there is ample evidence that attests to the fact that students with access to settled housing have better educational outcomes than those with less settled housing. This paper examines tertiary students’ housing needs and preferences, towards providing them with suitable and stable accommodation during their study duration. A 26-item online questionnaire was administered to students enrolled at two regional universities in Australia. Participants were asked to choose their needs and preferences from eleven housing attributes, and rate them from ‘most important’ to ‘least important’ need. The results were analysed using SPSS. The results of the survey from both universities indicate that students’ most important need was for affordable accommodation (i.e. the lowest cost for rent) and accommodation offering recreational facilities rated the least important. This study fills a gap in understanding student priorities in housing in regional universities and offers insight to individuals and institutions involved in or intending to develop student accommodation on how to properly target and satisfy this sector. The research findings has wider application to regional or urban-based universities in Australia and globally.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 source (direct Gemma or distilled Codex), 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".