Bibliographic record
Abstract
This paper is a narrative account of the conversation that took place at Pinar’s house, on April 4, 2023, focusing on a few themes that emerge from his 2023 book A Praxis of Presence in Curriculum Theory: Advancing Currere Against Cultural Crises in Education as well as the dialogue between us, including “subjective presence,” “study,” and “knowledge of most worth”. This paper hopes to experience Pinar’s calling not only in reverberating textual conversations but also in the author’s embodied lived experiences in the interview. This paper invokes several lived moments the author shared with Pinar and gives a glimpse of the person behind his text, in other words, to humanize the text. This would echo the humanist emphasis embedded in the reconceptualization of curriculum studies. This interwoven feeling, reading, thinking, and writing, I believe, are in itself a very pedagogical attempt to “concretize” the abstract and go beyond and behind the text. This article concludes with a discussion of the implications of embracing the subjective presence for teachers’ pedagogical praxis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.027 | 0.021 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.017 |
| Insufficient payload (model declined to judge) | 0.003 | 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".