Mrs. Klein and Paulo Freire: Coda for the Pain of Symbolization in the Lifeworld of the Mind
Bibliographic record
Abstract
Abstract The preceding symposium articles speculate on the psychosocial dynamics of discrimination as reverberating with grief, mourning, melancholia, and denial. They invite a psychoanalytic paradox on the fate of inchoate loss and its complex relation to oppression and depression: constellations of attachment to loss met with its social and psychical disavowal render inexpressible to the other the work of mourning and drive its myriad expressions. A different way of putting the dilemma is that grief calls upon symbolic equation (collapse of subject with object) and the pain of symbolization (contingency without certainty). Deborah Britzman's coda reads the psychoanalyst Melanie Klein's consideration of depression as the origin of the human condition with Paulo Freire's call to educators for a radical humanization to release oppression. Between Freire's Pedagogy of the Oppressed and Klein's Love, Guilt, and Reparation, the coda traces a signifying loss that attests to the entwined roots of the self/other matrix with attention to the needed fluctuations within interiority and exteriority, loss and the depressive position, illness and health, and psychoanalysis with pedagogy.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.020 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".