Still We Resist: Reflections on Our Tenure as Editors-in-Chief
Bibliographic record
Abstract
Editorial. On December 14 of this year, we will conclude our tenure as editors-in-chief of Affilia: Journal of Women and Social Work. In pondering this, our last editorial, we have been reflecting on those tumultuous years under the Trump presidency, a time during which some of our worst fears for the political landscape of the United States have come to fruition, and the centuries-deep wounds of systemic inequalities in our communities have been once again laid bare. The past few months of the pandemic have simultaneously isolated us from family, friends, and colleagues while requiring us to provide unparalleled levels of support and care for them. The continued killing of black, brown, and Indigenous bodies at the hands of the police has incensed us, even as we were heartened by the global masses who rose up against such injustices, all the while grappling with the financial, physical, and emotional wreckages wrought by the pandemic. The terrifying storms, floods, and fires that have become commonplace in many regions of the world are insistent reminders of an apocalyptic climate crisis whose effects also, predictably, land most heavily upon those same marginalized bodies and communities (Bhuyan et al., 2019). The death of Justice Ruth Bader Ginsberg, which reached us in the midst of writing this editorial just weeks before another U.S. presidential election, came to us as a blow to the solar plexus. We had not realized how much we had relied on her embattled body and the towering feminist judicial mind it housed to persist as bulwark against at least some of the rising tides of violence continuously encroaching upon our own gendered and racialized selves.
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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 | 0.061 | 0.222 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.013 | 0.009 |
| Scholarly communication | 0.040 | 0.023 |
| Open science | 0.008 | 0.006 |
| Research integrity | 0.030 | 0.037 |
| Insufficient payload (model declined to judge) | 0.026 | 0.022 |
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".