Bibliographic record
Abstract
The main purpose of this research project is to develop a comprehensive understanding of the effectiveness of the recruitment strategies used by some Vancouver-based school districts in terms of their impacts on Chinese students’ choice of high schools, and enrollment decisions from the perspective of administrators in charge of international departments. Data were collected from interviews with administrators from two Vancouver school districts and from on-line documents. Data were analyzed by using a pull-push model (Chen, 2006), which led to the formulation of recommendations for possible improvements for Vancouver-based School Districts with respect to effectiveness of promotional activities. The research findings reveal quality of Canadian education, inclusive Canadian environment, and Canada policy toward international students as pulling factors in attracting Chinese students. Specifically, proximity to China is an important factor in pulling Chinese students to Vancouver area from the perspective of administrators. In particular, the findings suggest that websites, agents, and seminars are effective promotional tools used by participating school districts in highlighting these pulling factors. The nature of the recommendations made to participating districts is to emphasize pull factors when conducting seminars or designing brochures and websites in attracting international students from China.
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 | 0.039 | 0.058 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.136 | 0.116 |
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".