Rural Versus Urban Students – Differences in Accessing and Financing PSE, Their PSE Outcomes and Their Use of Distance Education Research Projects
Bibliographic record
Abstract
The most significant finding of the report lies in the relationship between distance from PSE institutions and PSE participation and type of institution chosen. Generally speaking, distance from PSE institutions or rural residency (the two are highly correlated) have important effects on the PSE decisions and outcomes of youth. These impacts vary inversely with income, that is to say, the lower the level of parental income, the greater the impact. Youth from rural communities beyond commuting distance to a PSE institution are less likely than youth from urban communities of comparable income levels to enrol in PSE; however, the gap increases significantly when rural families’ incomes fall below $40, 000 per year. Moreover, regardless of income, they are more likely to enrol in a college if a university is not located within commuting distance (our analysis of YITS data also found substantially higher numbers of rural students in colleges than in universities). Distance does not appear to have a major effect on the choice of the field of study; however, there does seem to be some major differences between urban and rural students’ post-graduation incomes, at least among those who choose to borrow to finance their education.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".