Bibliographic record
Abstract
Narratives, both individual and collective, are a primary embodiment of our understanding of the world, others, and ultimately ourselves. As a receptive and a creative activity, they tell us how we are always already caught up in the enacting and re-constructing of stories. Here a Romani narrative, a collective identity constructed through negative inflation, exile, and splitting, is read through the lense of a “scapegoat” complex. Such a reading points to the way we are split between any form of “us” and “them” – conscious and unconscious, light and dark. Non-Roma or Gadje, then, are not separate from this “other” but are co-creating and co-living this identity and narrative. Addressing the unconscious, personally and collectively, becomes our ethical responsibility so that we become aware of both our shadow and the other with whom we manifest (and blame). In attending the “problem” of the scapegoat, I hope to extend not only the discussion of difference in teaching and research but also in our social or political response toward people, in particular the Roma, and other ethnic and visible minorities who have been denied rights, persecuted and discriminated.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".