Bibliographic record
Abstract
This article describes my tumultuous journey studying imagination in a graduate leadership seminar using an arts-based pedagogy called Performative Inquiry. Focusing on my own teaching and learning in this course, I share insights that inform my future teaching and can support colleagues interested in exploring imagination with their students. I accepted risks associated with arts-based performances and entered a shared space of vulnerability with my students. My struggles with resistance were real, and so too was the realization of the important role vulnerability plays in imagination-focused (leadership) education. I suggest that Performative Inquiry offers other (leadership) educators a powerful pedagogy and methodology for understanding imagination in their own lives and inquiring into their leadership education practices. Arts-based practices allow learners to feel their own imaginations and experience possibility by accepting invitations to be vulnerable, performing learning in a range of productive and generative ways.
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 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.008 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.013 |
| Insufficient payload (model declined to judge) | 0.068 | 0.045 |
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".