Auto/Ethno/Graphic Bricolage as Embodied Inter/Culturalism: Dis/Locating Stories of Becoming in Encounters With the Other
Bibliographic record
Abstract
This provocation emerges from my experience of a recent flight home from the Middle East. As our plane soars over the Persian Gulf and Iraq I stare out the window at the human and physical landscapes below. A flood of memories of lived experiences in Iran and other countries in this region soon overwhelms me – a disturbing tangle of personal stories and public histories that call into question my teaching and academic work. Dwelling in the tension-filled spaces between the writing woman and the written woman, I juxtapose texts, images, and academic theory to trouble the preponderance of binary language circulating in the mass media that closes down possibilities for inter/cultural relations both locally and globally. This auto/ethno/graphic bricolage draws upon post-reconceptualist theorizing to engage the im/possibilities of an embodied inter/culturalism as curriculum of hope, toward expanding the multicultural imagination.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.014 | 0.045 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".