Bibliographic record
Abstract
The challenges of teaching English to late adolescents are considerable and far-reaching. Worn pedagogy, endless tests and limited funding for books often results in students quitting reading fiction altogether. Their underdeveloped vocabulary and poor writing skills remain. Yet we are also given the opportunity to inspire students to love literature and its insights. Our own keenness helps as does eliciting ideas from seasoned colleagues. Reading educational theorists and literary critics is rewarding, but theorists are often more philosophical than pragmatic and teaching guides often lack a social context. Books about English that are both rigorous and useful are rare. However, there's a new one just out and it's terrific. It's Richard W. Bevis' The Time Machine and the Domaine; the Origins and Function of imaginative Literature. It sounds ‘heavy,’ but it’s not. In nimble and erudite prose. Bevis considers the questions that all English teachers face when standing before new students. “Why do we have literature and how do we use it?” and how does a writer present aspects of life's experience such that reading may become “a world or great adventure?” His analysis not only offers new views of the social functions of literature, it also reveals some surprisingly unique ways to present its structure and meaning.
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 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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".