Bibliographic record
Abstract
Abstract For more than a quarter of a century, Pat Schneider has helped writers find and liberate their true voices. She has taught all kinds--the award winning, the struggling, and those who have been silenced by poverty and hardship. Her innovative methods have worked in classrooms from elementary to graduate level, in jail cells and public housing projects, in convents and seminaries, in youth at-risk programs, and with groups of the terminally ill. Now, in Writing Alone and with Others, Schneider’s acclaimed methods are available in a single, well-organized, and highly readable volume. The first part of the book guides the reader through the perils of the solitary writing life: fear, writer’s block, and the bad habits of the internal critic. In the second section, Schneider describes the Amherst Writers and Artists workshop method, widely used across the U.S. and abroad. Chapters on fiction and poetry address matters of technique and point to further resources, while more than a hundred writing exercises offer specific ways to jumpstart the blocked and stretch the rut-stuck. Schneider’s innovative teaching method will refresh the experienced writer and encourage the beginner. Her book is the essential owner’s manual for the writer’s voice.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.073 | 0.030 |
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".