Bibliographic record
Abstract
North Dakota, large in territory and sky, light in population. Grand Forks, a small city on the banks of the Red River (which famously runs north), a university town, located on the far eastern border of the state and, in latitude, some 60 miles to the north of Quebec City, Canada. In the winter, snow crystals glint in the air even on sunny days. The first semester I spent at the university (1982), euphemistically known as the Spring Semester, temperatures were often 20 or more degrees below zero and once dipped to-40º (without factoring in the wind chill). Grand Forks, ND, might not seem to the uninitiated a likely locus for revolutionary thinking about education and social action. Yet, in the period from the late ’60s until well into the ’80s, it was exactly that. 1972 I first met Vito Perrone at what turned out to be the charter meeting of the North Dakota Study Group on Evaluation (NDSG). The year was 1972. I wasn’t previously acquainted with Dean Perrone, though as a resident of Vermont, another rural state, I knew that in the late sixties he upended traditional teacher education to create the New School of Behavioral Studies at the University of North Dakota. The mission of the New School was comprehensive, including all levels of education. Among its aims was an exchange program that sent master’s interns into rural North Dakota schools as temporary replacements for the many North Dakota teachers lacking four-year diplomas. The teachers, in turn, rotated to the university to take the courses required for a baccalaureate degree, bringing with them their years of classroom experience. Ranked 50th among the states in the educational preparation of teachers, a specific aim of the exchange was to improve North Dakota’s educational standing. Of further
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.025 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.008 | 0.017 |
| Insufficient payload (model declined to judge) | 0.014 | 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".