Bibliographic record
Abstract
Literature Quizzes are an integral part of the Southwell School Library programme. Students read widely, hoping to represent us in the annual Kids’ Lit QuizTM (www.kidslitquiz.com ). In this time of electronic entertainment entice your students to enjoy literature, books and ebooks. Reading encourages empathy with others whose lives and situations differ, global awareness, and knowledge of history. Myths and legends influence cultural practice and social realism helps them cope with life’s problems. Reading is a resource for our humanity. At this workshop play brain-training games. These will be given away along with signed books from New Zealand authors. Learn how to write quiz questions and select teams. Hear how we use cognitive technology to help students retain and retrieve literary information. Make Lit Quizzes part of your library programmes and see your readers grow exponentially. There may be a regional of the Kids’ Lit QuizTM near you!
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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 | 0.007 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.017 | 0.008 |
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".