Expanding the Edges of Narrative Inquiry
Bibliographic record
Abstract
This captivating book presents innovative answers to the question: why storytelling? Each chapter represents leading edge narrative research designs from Arthur V. Mauro Institute for Peace and Justice in central Canada, one of the world’s leading academic programs for Peace and Conflict Studies (PACS), and a major contributor to PACS scholarship. The authors are candid and offer inspiration for other scholars seeking groundbreaking ideas for their own research design while offering profound expansions to the current PACS literature. The scholarship reflects a diversity of ideas, passions, approaches, disciplinary roots, and topic areas. Each chapter explores different and critical issues in the field of PACS through various forms of storytelling, while providing recent original research designs for the future development of the field and the education of its practitioners and academics. This volume, co-edited by three of the early graduates of the program, presents and explores a number of these issues across the broad spectrum of Peace and Conflict Studies. Contributors to the book are recognized scholars and practitioners in their respective fields. The book has a wide audience, targeting those particularly interested in tackling and understanding old conflicts in new ways, and for those seeking to learn at the growing edges of PACS, at the undergraduate, graduate, and post-graduate levels.
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 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".