Solidarity and Disruption Collective Organizing In Computing II
Bibliographic record
Abstract
This workshop responds to the incredible growth of corporate tech power - including during a deadly pandemic - and the growing need for tech workers of all stripes (including researchers/academics) to build grassroots power. This workshop’s twinned themes of solidarity and disruption acknowledge that solidarity is vital but not sufficient to enact the structural changes we need. Disruption— in the form of sit-ins, strikes, refusal, and direct action—has become a necessary condition in the face of technology corporations’ greed-driven expansion towards militaristic, techno-totalitarian futures. In this one-day workshop, we will bring together tech workers, researchers and activists from academia, industry, and community-based organizations to extend conversations that we began in two workshops last year. We will further explore avenues and approaches for action, particularly to support practitioners’ and activists’ objectives, and connect participants with concrete opportunities for on-the-ground action.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.024 |
| Scholarly communication | 0.015 | 0.011 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".