Curriculum or Common Sense? An Exploration in the Classroom Production of Useful Knowledge
Bibliographic record
Abstract
The relation among instrumental knowledge, practical understanding, and critical insight has been examined in a wide variety of contexts, including workers' study institutes of I 9th century England (Johnson, 1979), the public school in post-World War I middle America (Lynd and Lynd, 1929), and third-world literacy programs (Freire, 1973). A recurrent theme is the tendency of instrumental or technicist concepts of education to suppress those interests and concerns of students which might lead to their developing critical insights into their situation. In other words, certain attempts to make education more practical or useful may, ironically, make students less able to form autonomous judgements about their social situation and more dependent on official definitions of it. This paper explores some problems associated with attempts to implement a curriculum geared to imparting useful knowledge. In particular, it focuses on the relation of practical understanding and critical insight to the instrumental tendencies associated with a recent curriculum innovation, life skills education, which has found wide application in educational and training contexts in Canada. In the pages which follow, I consider some main features of the life skills approach and raise issues connected with the social dimensions of school curricula of this kind. I then turn to a case of teaching skills for everyday living in the setting of a secondary school classroom.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.005 | 0.036 |
| Scholarly communication | 0.012 | 0.017 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| 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 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".