Landscapes of Injustice, Landscapes of Repair (Editor's Introduction)
Bibliographic record
Abstract
The ongoing Landscapes of Injustice, Landscapes of Repair seminar series features activist and scholarly work with an emphasis on thinking from the margins.The series aims to develop critical methodologies grounded in feminist and decolonial practices to address political and environmental degradation and center the knowledge of those most affected by it.The current Dispatches in this issue detail four events in the series in spring 2023: Infrastructures of Harm, Communities of Knowledge, and Environmental Justice with Marco Armiero and Divya Gupta; 1 Climate (In)justice and Advocacy: A View from the Humanities with Belinda Walzer and Savannah Paige Murray; 2 Speculative Fictions for Decolonial Futures with Bodhisattva Chattopadhyay and Jane Alberdeston Coralin; 3 and the workshop, Postcolonial DH: Critical Cartographies, Decolonial Archives, and Humanities for the Public, with Alex Gil Fuentes.The Landscapes of Injustice, Landscapes of Repair series began in 2022 with a workshop developed and led by Dr. Nikiwe Solomon from Environmental Humanities
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".