Bibliographic record
Abstract
he must study teeth and gums, etc. The activity of dentistry must make technology match his patients ’ inner organismic requirements or standards. But the analogy also illustrates an important difference between these two activities. Dentistry is done with technology, and progresses in efficiency based on such improved technological tools. But Education is not “done ” with technology. “Education ” (noun) is not a practice, but a hypothesized set of guidelines to enhance Life itself (as John Dewey argued). Educating and teaching (verbs) are practices, it is true, and they can use technological tools as well, but still such practices cannot be fully undertaken by means of technology, as can dentistry. Admittedly, a good “chairside manner ” for the dentist is desirable, but in Education, that human connection must be the hypothesized actual practical focus for the teacher. It cannot be secondary, as in dentistry. As Brickell puts it, The three most important ingredients in the school setting are the student, the teacher, and the length of time they are together … Once those three are established, researchers will discover little if any significant difference among various teaching methods (1982, quoted in Elkind, 54). Unfortunately, however, politics and economics, which drive public schooling, tend to ignore the first part of my original analogy, while embracing the second. As Livingston observes, “Instead of imaginatively constructing meaning, the child becomes a computer, trained, programmed, and tested for the job market ” (1994, 133). Here the standards that guide educating become external and social, not internal and organismic, and the child itself then becomes the technology used to create social “progress”. Witness the Minister of Education for New Brunswick in 1993, who said that New Brunswick schools have “got to be industry driven”, and “the first mistake is assuming schools and teachers will teach our kids”, since to produce “better prepared students ” or “products”, is “too important to be left just to educators”. The McKenna
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".