Bibliographic record
Abstract
Drawing on queer and feminist Digital Humanities (DH) and Indigenous, antiracist, and intersectional approaches to publishing, this pedagogy piece reflects on a course designed and taught in Fall 2018 titled “Intersectional Feminist Journal Praxis.” Students read intersectional readings on publishing while creating their own journal through Open Journal Systems Software (OJS). Employing principles of collaboration and praxis, students worked in teams around specific tasks like a call for papers, peer review, copyediting, and introduction-writing while employing critical publishing practices such as remaining reflexive about, for example, accessibility and power inequalities in processes of knowledge production. Their end product was the publication of the first issue of the journal they themselves created by the name of Intersectional Apocalypse (https://journals.lib.sfu.ca/index.php/ifj). This piece discusses this pedagogical DH experiment, grounding it in histories of anti-oppressive publishing endeavors and in students’ own words and reflections on the course.
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 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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.024 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.011 | 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 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".