Misleading the Students: Conceptual Difficulties in Woolfolk’s Account of Motivation
Bibliographic record
Abstract
INTRODUCTION It is difficult to help student teachers come to understand the concepts and issues basic to the social, psychological, and philosophical foundations of education in these times. Some on the right, such as Alasdair MacIntyre, regard the social context as having so far degenerated that all that is left is “emotivism” and a confusion of tongues. Some of the radical left, such as Herbert Marcuse, regard capitalism as so constricting that one needs to get beyond tolerance, yet one sees no hope in so doing. Some of the liberal left, such as Richard Rorty, believe that the system is now controlled by greedy and selfish people. And even those who wish to get beyond the labels “right” and “left,” such as Jeffrey Stout, fear that the language of the market is leaking into other practices and corrupting them.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.028 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".