Staying Connected Across the Wall During the COVID-19 Pandemic
Bibliographic record
Abstract
Formed in 2011, the Walls to Bridges (W2B) Grand Valley Institution for Women (GVI) Collective is comprised of inside and outside W2B alumni and instructors.Together, we train W2B instructors and act as the steering committee for the National W2B offi ce using shared decision making through a collaborative circle process and creative activities.In this article, we write about the impact of COVID-19 on our group, tracing our methods for persisting through restrictive pandemic and prison policies to continue to build bridges to one another.We detail our process for creating two collaborative projects that highlight the creativity of the GVI collective -A Book of Collective Survival in Pandemic Times and the 10 th Anniversary Presentation Collaboration.We off er these as reminders of the power of a collective that chooses to reach out for each other during diffi cult times as lessons to take forward after the pandemic is done.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.019 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 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".