Loose among the Literati: Wired Writers and the Virtual Practicum.
Bibliographic record
Abstract
recall an article in the Fall 2001 issue in which Christine Uy and I reported on one of the ancillary programs of the Writers In Electronic Residence (WIER) program. In that case, we reported how the experience of WIER was extended to include the integration of a substantial collection of contemporary Canadian authors’ works into a school library and literature program, and how these were supported by regular face-to-face visits by authors selected from this group. In this article, I am pleased to team up with Sudha Takaki to report on another of WIER’s ancillary projects, “The Virtual Practicum,” which provides online practice teaching placements to pre-service candidates. WIER offered its first virtual practicum in 1989 through the former Faculty of Education, University of Toronto, and has since expanded to include programs at several institutions; other initiatives have appeared elsewhere, developing notions of what virtual practica might be. Takaki participated in WIER through OISE/UT’s “Internship Program,” which involves pre-service candidates in experiences beyond the institution. She worked online
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.033 | 0.058 |
| Scholarly communication | 0.023 | 0.013 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".