Bibliographic record
Abstract
A personal reflection on how Shira Leuchter’s desire to preserve existent family memories led her to create the live art performance All the Things I’ve Lost, which she performed with her mother, Joyce. All the Things I’ve Lost was commissioned by the Gardiner Museum in Toronto and premiered in August 2016. Through performing the piece, Shira discovered that casting her mother to help her recreate lost childhood objects prompted audience members to share their stories of loss with her during impromptu sessions after each performance. Acknowledging the apparent need for sharing and companioning stories of loss, Shira created the live art performance Lost Together. Lost Together premiered as part of the SummerWorks Festival Lab in 2018. While Shira and co-performer Michaela Washburn recreate and reimagine lost things for audience participants during this intimate performance, Shira recognizes that they can never be successful in resolving loss for their audience participants. Instead, they can hold the weight of the loss with their audience and offer community and connection. Shira contends that collaborating with audiences and leading with tenderness is a radical act of performing care in a culture that prizes individualism.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.175 | 0.066 |
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".