Creating Transformative Spaces in Education: Facing Humanity, Facing Violence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper considers the difficulties that accompany projects in education variously configured around a multicultural or intercultural label, particularly when they are built upon, for example, idealised conceptions of humanity, notions of the common good and dialogue, or ideas of recognition. My premise here is that, while such idealisations may be constructed with the best of intentions, they occlude discussions of how to face the violent realities that can also be part of social interaction. My focus here is on the existential conditions that frame our encounters with other people, and how such existential concerns lead us to confront more openly the violence that can inhere in such encounters. Beginning from this existential position, I argue, actually invites alternative ways of formulating transformative work in education, namely a focus on the present. Secondly, I turn to explore the transformative spaces created by performance artist Marina Abramovic, and how her projects reveal what we are up against existentially when it comes to facing humanity in the here and now, in all its messiness. And, finally, I make the suggestion that an education committed to the existential conditions of facing humanity can be built on a reconceptualization of conversation, as opposed to dialogue. Here I argue that conversation offers the kind of potential for transformation in its open-endedness and anarchic sensibilities.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it