Bibliographic record
Abstract
In March 2020, protestors made their anger known when Bailey Theatre in Camrose, Alberta announced that the indie rock band Small Town Artillery would perform at their venue. This band openly supports Indigenous rights and opposes pipelines through Indigenous lands. The circumstances around this performance event serves as the basis of this article’s examination of the role of a community theater, not only as an important third place, which contributes to the cultural and political vitality of the region, but also as a site for potential disunity. In an era of increasing political polarization, third places like community theaters, once considered essential to civil society and democracy, are often finding they have become contested spaces. The research findings demonstrate that the Bailey Theatre has become an important center of activity that fosters community connection, celebrates shared values, debates differences, and explores what it means to be human. However, as this case study demonstrates, venues can also be sites for community disunity and the contestation of competing ideologies. Using qualitative methods and building on the literature on community and third places, this article argues that to ensure their role in fostering a vibrant cultural scene and creating safe spaces for the celebration of diversity and civil society, community theaters must implement practices that foster civility and serve all their communities even if they run the risk of sparking moments of community discord.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.019 |
| Scholarly communication | 0.017 | 0.005 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".