The Possibilities and Limitations of Importing a Concept. Canada’s First-Generation Students
Bibliographic record
Abstract
Mass access to higher education in developed countries has attracted a more diversified student population, with an increasing amount of women, older students, and students from ethnic minorities and socially disadvantaged backgrounds. American academics have coined the concept of “first-generation students” to refer to students whose parents did not attend postsecondary education. This paper shows the heuristic weight of this concept outside the United States from a longitudinal survey of young people in transition by Statistics Canada. While accountability is part and parcel of the daily management of education, and educational indicators are ever-increasing, the presence of first-generation students could be used to measure how much educational systems have opened up.
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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 | 0.147 | 0.214 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.012 | 0.069 |
| Scholarly communication | 0.022 | 0.036 |
| Open science | 0.008 | 0.019 |
| Research integrity | 0.007 | 0.017 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".