Bibliographic record
Abstract
Introduction, by Max Stephenson, Jr. and A. Scott Tate 1. Making Beauty, Making Meaning, Making Community, by Arlene Goldbard 2. Rivers and Bridges: Theater in Regional Planning, by Jon Catherwood-Ginn and Robert H. Leonard 3. One New York Rising Together? Arts and Culture in Neighborhood Ecosystems, by Jan Cohen-Cruz 4. Sustaining Emergent Culture in Montreal's Entertainment District, by Anjali Mishra 5. Digital Storytelling in Appalachia: Gathering and Sharing Community Voices and Values, by Holly Lesko and Thenmozhi Soundraajan 6. Shaping the Artful City: A Case Study of Urban Economic Reinvention, by A. Scott Tate 7. Community Cultural Development as a Site of Joy, Struggle, and Transformation, by Dudley Cocke 8. A Dialogue on Dance and Community Practice, by Liz Lerman and Jawole Zollar 9. Assessing Arts-based Social Change Endeavors: Controversies and Complexities, by Kate Preston Keeney and Pam Korza 10. Theater as a Tool for Building Peace and Justice: DAH Teatar and Bond Street Theatre, by Lyusyena Kirakosyan and Max Stephenson, Jr.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.047 | 0.011 |
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".