Bibliographic record
Abstract
In 2007 Queen’s University tore down the twenty-foot limestone walls surrounding Kingston’s old Prison for Women, at one time the only Federal Penitentiary for women in Canada. When the building’s new owners destroyed the walls, Queen’s students, and Kingstonians alike, stopped on their journeys to and from ‘West Campus’ to observe the revealed “Medieval Fortress” and ponder what had once existed. Since 2002 I have been researching the unique history of this building and the stories of the women who once lived, worked and died here. By combining this research with my theatrical background I have been creating a theatrical production by leading an ensemble of six women through a devised theatre process. It is my hope to further break down the barrier between Kingston and the unique history and culture that existed here from 1934 to 2000. As an ensemble we have been working with stories, movement and song to bring the piece to life. The P4W inmate magazine “The Tightwire” has provided us with original stories, poems, songs, articles and artwork created by the inmates themselves. By integrating the words of the female inmates we hope to paint an earnest picture of what life was like behind the walls of the P4W. We will be performing this piece in the Rotunda Theatre on Queen’s Campus on March 31st and April 1st.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.028 | 0.018 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".