Response to "Anxious Academics: Mission Drift and Sliding Standards in the Modern Canadian University"
Bibliographic record
Abstract
Joseph Galbo has written a poor review--not by panning Ivory Tower Blues, but by misrepresenting its central thesis: that grade and inflation have conditioned a crisis wherein students and professors are disengaged in ways that threaten the quality of liberal-arts education. Galbo has done a disservice to the readers of this journal for this mischief as well as for misframing other arguments. We cannot possibly address all of his inaccuracies in the space we have been allotted. However, we will point out several of his most egregious mistakes. The most fundamental error Galbo makes stems from his failure to understand that the book was written for several audiences. In introduction, we specified these audiences: first and foremost (p. 13) the general public, especially parents with children in the system; but our third audience, in this order of priority (p. 14) was other professors. Apparently thinking we wrote a book strictly for academics, he claims disappointment that the book wasn't more intellectually challenging and that we made reference to some popular social science literature. Galbo claims that we present a pet theory, when in fact we drew on the massive research carried out by the National Survey of Student Engagement (NSSE) and the Cooperative Institutional Research Program (CIRP). He should have checked references, especially the publications of George Kuh, the Director of the NSSE, to see that academic and its associated disengagement compact is not pet theory, but a documented problem in the United States, that was exposed as worse in Canada when the NSSE was carried out here beginning in 2004. Rather than admitting this, Galbo goes on to claim that we present no compelling that is a problem in universities. To the contrary, the evidence is overwhelming that academic has been increasing since at the least the 1980s (from the CIRP studies; the NSSE picked up the trend in 2000). Even without looking at the evidence produced by these massive research undertakings, Galbo should have realized that because hundreds of universities across the United States and Canada are participating in the NSSE, is already recognized as a serious problem that needs to be monitored and addressed. In Canada, student enrollments have risen 50 percent since the 1980s, budgets have dropped by 30 percent, and faculty complements have hardly grown at all. Does Galbo really believe that this had no consequences? A rather facile reading might lead one to think that we are blaming students, and in pushing this superficial interpretation of the book, Galbo fails to acknowledge structural analysis. Contrary to his claims, we repeat throughout the book that we are not blaming students (e.g., pp. 8, 103), and we trace the history of structural changes of the university from clerical training to the most recent era of credentialism, where we locate the credential mart. Never mentioning this, Galbo claims that we are ahistorical because we do not focus on women, minorities, and those from lower social class origins, whom he notes were previously excluded from attending university (by the way, we include ourselves in two of these three groups). …
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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 | 0.018 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.043 | 0.025 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.007 | 0.008 |
| Research integrity | 0.021 | 0.027 |
| Insufficient payload (model declined to judge) | 0.008 | 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".