“You ask many questions, but you don’t give many answers”: Embracing the Mess in Conflict Studies Classrooms
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 reflects on the author’s experience of teaching oral history and related qualitative methods to students in Conflict Studies, a program oriented around intervening in conflicts and effecting positive change in the world. It examines how students have engaged with the complexities of a postmodern approach to oral history that embraces uncertainty and the messiness inherent in interviewing. How do students understand what it means to embrace a plural notion of “truths”? How can this be a constructive force in their lives that helps them see the world in more complex ways, rather than making everything so contingent that we can draw no meaning from it at all? Drawing upon the author’s own experiences as well as the recorded reflections of four former students, this paper shows the challenges and rewards of encouraging students to engage with these complex questions. It also warns that in the current political era of “alternative facts” and “fake news,” navigating such nuanced terrain must be done with caution.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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 it