An intellectual biography of Dwayne E. Huebner : biography, curriculum history, and understanding curriculum as theological
Bibliographic record
Abstract
William Pinar proposed that Dwayne Huebner may well be judged by future historians of the field as the most important mind in curriculum. Since his retirement from curriculum studies, Huebner has long been associated with theorizing curriculum theologically. Yet I believe that this articulation and engagement of his legacy needs further nuance and understanding. Using the biographical research method, this dissertation seeks to reframe Huebner’s theological legacy by contextualizing it through his lived experience and his significant ideas. This dissertation is divided into four parts. Part 1 examines the biographical method, focusing specifically on intellectual biography. Part 2 contextualizes his interest in theology by narrating the lived experience of Dwayne Huebner through interviews conducted with him as well as reviewing official professional documents. Moreover, I contextualize his engagement with theology in comparison with significant themes found in his scholarship in Part 3. This includes his educational creed, his ontology, and his understanding of knowledge and its forms. Part 4 reframes Huebner’s legacy for those seeking to theorize the curriculum theologically.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".