Playing 'Shame': One Technique for Introducing Text Analysis to the Literary Studies Classroom
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<p>A former professor of mine, now gone to his just reward &ndash; a character who one might never imagine to find in a David Lodge novel, and yet he was noted in one as a poor soul banished in the late 1960s from glitzy, big-shoulder US academic culture to the pastoral Canadian prairies we all know and love &ndash; gave me some of the most useful pragmatic advice I&rsquo;d ever received from an academic up to the point that I&#39;d received it. He suggested that all of us concern ourselves as much with the expanding of our own knowledge as we do with concealing those areas in which we have little expertise or experience. This was heady stuff for me (I was quite a few years younger, then), but it was an apt observation. And when I think of the focus of this panel &ndash; &lsquo;playing with text analysis&rsquo; &ndash; his words resonate....</p>
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it