Bibliographic record
Abstract
We are honored to commemorate the 10 th Narrative Matters conference--taking place on the 20 th Anniversary of the inaugural event in Toronto in 2002--with this Special Issue of Narrative Works.Further, we appreciate the invaluable guidance and support of Bill Randall, the founding editor of the journal, and the journal's new editor, Kate de Medeiros.It would have been difficult to imagine how the world would look when the organizers of Narrative Matters 2018 handed the baton to us at the University of Twente in July of 2018; from a global pandemic, to the Black Lives Matter movement and a renewed push for racial and economic equality and justice, to the ongoing humanitarian and political crisis in Ukraine.Clearly, the importance of dialogue, and finding shared meaning through stories, is as important as ever--interpersonally, and internationally.Atlanta holds a deep connection to the United States Civil Rights movement, and in hosting the 10 th Narrative Matters--the first Narrative Matters in the US--we attempted to recognize this history with the theme of personal and social transformation, including with the keynote address of Derrick Alridge (forthcoming), and his ongoing work documenting the experiences of courageous
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.286 | 0.134 |
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".