Distance Students as Virtual Migrants: A Case Study from Atlantic Canada
Bibliographic record
Abstract
Distance learners are typically excluded from discussions of student mobility. This paper explores distance student choices and experiences, drawing on a study that included students who enrolled in distance education courses at a university outside of their home province. Findings from this study suggest that program and course considerations such as quality, accessibility, and reputation were of primary importance to distance learners. Program cost was also found to be influential in students’ decision-making. Overall, this study adds to the current literature on distance student enrolment choices, experiences, and expectations. It makes a significant contribution in identifying factors that may result in students’ enrolment in distance education outside of their home region, and that should be considered in university recruitment initiatives. Typiquement, les apprenants à distance sont exclus des discussions sur la mobilité des étudiants. Cet article explore les choix et les expériences des étudiants à distance en puisant dans une étude qui a inclus des étudiants inscrits à des cours à distance offerts par une université située dans une province autre que la leur. Les résultats portent à croire que, par rapport aux programmes et aux cours, les apprenants à distance tiennent surtout compte de la qualité, l’accessibilité et la réputation. Le cout des programmes entre également en ligne de compte dans le choix de cours par les apprenants. Globalement, cette étude ajoute à la documentation existante sur les choix de cours, les expériences et les attentes des étudiants à distance. Elle contribue de manière importante à l’identification des facteurs qui pourraient entrainer l’inscription par des étudiants à des cours ailleurs que dans leur région de résidence et dont devraient tenir compte les initiatives de recrutement à l’université.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.028 | 0.006 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| 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".