Radical Empathy in Archival Practice Poster and Postcards
Bibliographic record
Abstract
This poster and accompanying postcards were created by Gracen Brilmyer for the Journal of Critical Library and Information Science (JCLIS) special issue on Radical Empathy in Archival Practice. The poster and postcards visualize and embody the four archival relationships proposed by Michelle Caswell and Marika Cifor in their 2016 Archivaria article, “From Human Rights to Feminist Ethics: Radical Empathy in Archives,” in addition to three new relationships proposed by others. You are encouraged to complete this poster by: Filling in each of the 7 illustrated relationships (dotted line box) on postcards Mailing postcards to someone who embodies this relationship Appending the postcards to the poster, or writing in the relationships Additionally, since poster printing can be cost prohibitive, we have also included a "Printer-Friendly" version of the poster, which can easily be printed on multiple 8.5" x 11" sheets of paper and assembled. Pre-print first published online 05/21/2021
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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.261 | 0.041 |
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".