Education for an Urban America: Ralph Tyler and the Curriculum Field
Bibliographic record
Abstract
If, as some have maintained, one’s prominence as a scholar often depends as much on one’s longevity as on anything else (Goode, Furstenberg, and Mitchell, 1970, p.l), no individual has more of a claim to eminence within the curriculum field than does Ralph Winfred Tyler. Throughout the last quarter century, no one has played a greater role in defining the issues about which curriculum workers write and debate than has Tyler. He is often seen, it seems, as the great ‘synthesizer’ of the ideas of such diverse curriculum theorists as John Dewey, Franklin Bobbitt, W.W. Charters, Edward Thorndike, and the McMurry brothers (Eisner, 1985, pp.11-12; McNeil, 1981, pp.339-340; Schubert, 1980, pp.105-110; Tanner and Tanner, 1980, pp.83-88). In this vein, one contemporary educator has argued that the so-called rationale for resolving curriculum problems that Tyler spelled out in his 1950 syllabus for Education 305 at the University of Chicago, Basic Principles of Curriculum and
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".