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
Teaching crisis management is both fascinating and frustrating. It is fascinating because crises, by their very nature, are spectacular, dramatic, and intense; immediately arouse the individual and collective imagination; and because everyone seeks explanations for what, at first glance, appears inexplicable. It is also fascinating because educators are exposed to a transdisciplinary and transborder field of studies with wide-ranging ramifications. Yet it is frustrating because educators must often deconstruct the popular perception that crises are rare, improbable, and unpredictable phenomena, often leading individuals to feel powerless and fatalistic. It is also frustrating because of the lack of knowledge in the field itself, at three levels: conceptual/theoretical, practical, and reflective. This article highlights the teaching challenges in this rich and diversified field at each of these three levels and examines three teaching tools to address them: case studies, crisis simulations, and the reflexive journal. The authors also consider that a crisis cannot be viewed as a homogeneous concept. With the help of Gundel’s crisis typology (conventional, unpredictable, intractable, and fundamental crises), the authors present promising teaching approaches to deal with each of the three aforementioned teaching challenges, explaining how each approach can be seen as a function of the four types of crises.
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 | 0.004 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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