Disengagement, Pedagogical Eros and (the undoing of?) Dialogic pedagogy
Bibliographic record
Abstract
Dialogic pedagogy is an approach to education influenced by Bakhtin, Freire, and others. It is an approach that is critical of conventional education, which tends to be didactic and alienating to students. Student engagement is made central as dialogue takes priority over standardization and core cannons of content. Dialogic pedagogy also emphasizes the importance of communities of learners where teachers are co-learners along with students as all parties work on problems together. I seek to raise challenges to Dialogic Pedagogy and these come from scholars working on the “conduct of everyday life” and from Charles Taylor’s notion of “strong evaluations”. The conduct of everyday life involves a focus on first-person subjectivities with an eye to their constitution in social and power relations. Strong evaluations enhance this discussion by addressing how people can engage in decisions that involve weighing options about the qualitative kind of person one is. I outline how education involves a conduct of everyday life where strong evaluations are promoted. Taking such an approach to education grounds two challenges to dialogic pedagogy. One challenge is that students are reticent to engage in strong evaluations and the modern identity is one disposed to disengagement. The converse challenge is that student engagement entails pedagogical eros, which is easily converted into power and abuse by a pedagogue.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.049 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 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".