The Eroding Standards Issue: A Case Study from the University of Waterloo
Bibliographic record
Abstract
The proposition is addressed that the mathematical skills of first year entrants into the Faculties of Mathematics, Engineering, Science and Applied Health Sciences at The University of Waterloo have declined. Analysis of a series of scores from a mathematics diagnostic test for new students suggests a decline over the period 1991-93 and possibly through to 1995. This reproduces a trend detected at The University of Western Ontario. By the mid-1990s, however, the scores level out. Many of the faculty members questioned in a survey also perceived a decline, and, independently of the time series data, informants pointed to the early 1990s as the critical period of decline. The feeling of being under pressure to adjust to declining standards by upward "belling" of grades varied greatly by faculty, being far more prevalent within the Faculty of Mathematics than in other faculties surveyed. The survey respondents claimed that most deficiencies in mathematics preparation in the high schools were remediable by working to alter the attitudes and expecta- tions of first year university students.
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.027 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".