Bibliographic record
Abstract
This research project examines some of the complexities of the Medieval work “Sir Gawain and the Green Knight” from the perspectives of both worldrenown scholars and laymen interviewees. The study uses professional instudio equipment to record responses to research questions asked of academics by long distance phone interview. In the same way, the researcher asks questions of a randomly selected public group and records the commentary with portable equipment. The researcher then compiles raw material from interviews in bricolage format. The result juxtaposes the original views of both prominent researchers and the public on controversial issues within the “Gawain” text. The study likens the complex issues of gender, public morality, community and capitalism occupying medieval audiences to the types of challenges society faces today. This comparison of medieval and modern issues show that historical literary works are of enduring value to the contemporary reader; works, like “Sir Gawain”, deal with a complex set of social issues in a way that encourages a multiplicity of readings and engages with various different audiences. As a way of reaching the broad audience concerned with these issues, the project arranges the interview feedback into a radio program format complete with medieval musical segueways. The program originally aired on CFRC, Queen’s Radio in two parts on March 28th and April 6th, 2006, respectively, and remains available online via www.chatterbook.ca. Professors from Canada, the United States and Europe have requested permission to use the project as a teaching aid.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".