Unconscious ties that bind – attending to complexes in the classroom: part 1
Bibliographic record
Abstract
ABSTRACT Recognized by few in theory and practice, unconscious dynamics affect all aspects of education, including teaching and learning, as well as assessment, coding, and teacher preparation. Jung proposed that the collective unconscious is akin to a very deep psychosocial well from which individuals, families, and cultures across time and place draw in order to organize and make meaning of life. If we accept this claim, then the ways we understand and attend to interpersonal dynamics within the classroom radically change. Here, in two conjoining parts, a case is made for the vital importance of acknowledging and working with the unconscious, particularly the cultural layer (Part 1) and the familial layer (Part 2) of the psyche. Attention in Part 1 is given to the social and political turn in Jungian psychology and its importance to the dramatically changing ethnocultural character of Canada’s classrooms (likewise with many countries today). The cultural unconscious, cultural complexes, scapegoating, and the critical intersection between groups and individuals are examined in relation to education.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.047 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".