This Sacred Moment: Listening, Responsibility, and Making Room for Justice
Bibliographic record
Abstract
When Ingrid Waldron asked me to create and share a summary of the excellent and juicy presentations and discussion at the symposium titled “Over the Line: A Conversation on Race, Place, and the Environment,” held in Halifax on October 27, 2017, I agreed right away. I’d planned to be at the symposium listening carefully and taking notes anyway. Little did I know that I had agreed to share my “hot take” verbally, in front of everyone, immediately after the final presentation! I’m much more comfortable sharing my thoughts on something after I have mulled it over for a day, a week, or—even better—a few months. The short series of small thoughts in this article are the closest I could come to synthesizing my impressions of the day, in that moment. The result is not comprehensive, but I hope it expresses the vulnerable and hopeful mood I was sensing, along with the appetite for deep resistance and change in the room at the end of a whole day of badass idea-sharing.
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 | 0.011 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.035 | 0.056 |
| Scholarly communication | 0.021 | 0.023 |
| Open science | 0.002 | 0.018 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".