Bibliographic record
Abstract
collectivity activities. Both companies reached out to their audiences by mailing out brochures and newsletters, holding open workshops, and inviting the community to view works in progress. 7 While At the Foot of the Mountain encouraged discussions after all its performances, Nightwood has tended to do this only in fairly controlled ways -for example, through feedback forms at "Groundswell," its annual festival of new play development, or at panel discussions with a moderator and guest speakers. Only recently, in its 2006/2007 season, has Nightwood started having "talkback" sessions after Tuesday night performances. The two companies were also similar in having a relatively large and active staff and receiving government funding through arts council grants. There is one marked difference between the two companies, however: Leavitt writes that when ATFOTM was invited to perform at "the prestigious 'Alternative Theatre Festival' in 1977, they declined because they suspected they would be a hit and that this kind of success would inhibit the work they want to do." While they received good reviews and grants, At the Foot of the Mountain members were said to "reject most traditional success indicators." 8 This has never been the case at Nightwood, which has actively pursued as much of a profile as it has been able to afford.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.034 | 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".