On-campus and off-campus student housing cooperation: a systematic review protocol
Bibliographic record
Abstract
eview question / Objective Focusing on on-and off-campus student housing, this systematic review aims (1) to systematically examine the current landscape of on-campus and off-campus housing for students and critically analyze the results of this research, and (2) to develop student-driven recommendations for future research and practices, further supporting student housing services at universities.Through a comprehensive synthesis of existing literature, this systematic review will provide detailed descriptions of the multifaceted dimensions of student housing and uncover valuable insights guiding policy decisions, institutional strategies, and future research directions.Rationale Student housing is an essential aspect of a student's academic journey.Housing types and living environments significantly influence students' well-being and academic performance.The landscape of student housing has undergone significant changes in recent years, due to factors such as COVID-19, urban housing crises, increased university enrolments, student diversity, and students' changing needs.The new and changing circumstances of student housing emphasize the need for adaptable and resilient housing solutions.To inform future research and practices, a systematic review of the existing literature is necessary to examine and understand the current and changing landscape of both oncampus and off-campus student housing.Condition being studied N/A.This systematic review is based on social sciences rather than health care.Thus, this review will not focus on health conditions or diseases.
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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 | 0.077 | 0.124 |
| Meta-epidemiology (narrow) | 0.006 | 0.009 |
| Meta-epidemiology (broad) | 0.024 | 0.021 |
| Bibliometrics | 0.030 | 0.024 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.086 | 0.010 |
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".