On the global polycrisis: Speaking up for the ethical imperative of Left, socialist politics in nursing
Bibliographic record
Abstract
Nurses know how to speak up. We bring powerful voices forward for justice, historically and currently, in all manner of forums local, regional, national, and global. However, we have not coalesced in any substantive way around the current global polycrisis of growing and blatant rights violations at the hands of governments’ alt-Right promotion of unfettered capitalism and hatred of marginalized and racialized peoples. This editorial provides a description of Left, socialist politics and Right-alt-Right politics for nursing, with a call for nurses to join mobilization for Left politics to confront the global polycrisis of vast inequitable and widening global economic and social inequalities and climate emergency.
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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 | 0.023 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.085 |
| Scholarly communication | 0.024 | 0.019 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.013 | 0.026 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".