Affecting education through portraits of the emotional world of learning
Bibliographic record
Abstract
The symposium consists of three presentations based on close readings of case studies of the lives of writers, teachers, scientists, psychoanalysts, and youth along with a coda on the crucial topic of why and how attending to the emotional world of teaching and learning involves the psychical procedures of destruction and creativity; refusals and acceptance; withdrawal and curiosity; and love and hate. The work of the symposium is to provide an affecting model of education dedicated to understanding the emotional world; develop a case study approach to analyzing crucial paradoxes of education; extend the growing field of psychoanalysis and education to the specificities of teacher education; and finally, to provide new approaches to thinking about teacher education through the lens of human development. Each presentation conceives development through intersubjectivity and as uneven, subject to regressions and creativity, made from experiences of continuity and discontinuity, and, all told as a response to the emotional situation of being with others. What joins the symposium is the problem of presenting the affecting qualities of the emotional world found in the question: Is the capacity to represent and understand one’s development a creative experience and itself a developmental phenomenon?
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.024 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".