Bibliographic record
Abstract
In this extract from, and commentary on, my master’s thesis, “The Brooch of Bergen Belsen: A Journey of Historiographic Poiesis” (winning York University Department of Education Best Major Research Paper 2010), I explore a single aesthetic experience, an encounter with a small hand-made floral cloth brooch donated to the Holocaust Memorial Museum. At the start of my inquiry, I had only the object—the brooch itself—my emotional reaction to it, and the few lines of text on a curated museum card. I wondered, how do we create “spaces for remembrance” (Simon 2005) and what are the implications for teaching, learning and living in a just society? How arewe accountable to Simon’s (2004) demand for “non-indifference?” Arts-based research methodologies such as historiographic poiesis have allowed me to merge the scholar and artist, to engage in research as an iterative process where deeper questions engender more complex and embodied responses, and to create an aesthetic intervention: an open, dialogic text and artworks that provoke new understandings of narratives previously overlooked.
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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.050 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".