Bibliographic record
Abstract
In this introduction, I will approach the special issue’s theme of positionality as informing critical reading approaches of North American literatures by and about minority subjects in a personal tone to match the required positionality statements in the essays. As an example, I will outline my own motivation for thematizing positionality after observing lived connections between my travels to Canada and the U.S. as well as becoming aware of how my family’s intergenerational experiences against the backdrop of transatlantic relations critically position myself. I will argue that reflections of one’s own positionality matter for researchers, while drawing from decolonial scholarship’s warningsagainst knowledge appropriation, extractivism, and a contemporary criticism of identity politics in an age of social protest. Instead, a responsibility towards the minority literatures that are being researched is posited in the essays included in this special issue from which self-reflexive statements are quoted in their original form. This special issue hopes to promote inclusive dialogues, beginning with self-positionings of global contributors within the field of North American Studies.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.335 | 0.205 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".