Bibliographic record
Abstract
MacLachlan, Patricia. Word after Word after Word. New York: Katherine Tegan Books, 2010. Print. Ms. Mirabel, a famous writer, starts visiting a grade four class regularly and has a profound impact on a group of five friends by encouraging them to write, even if it means breaking the rules that their teacher believes are essential (such as creating an outline). Ms. Mirabel’s core message that writing “word after word after word” can change your life strikes a chord with the five friends and, as their daily discussions under a lilac tree suggest, there is a lot they would like to change. Lucy’s mom has cancer, Evie wants desperately to find a new woman for her recently-separated dad, a new baby is entering May’s family, and Russell not only has to babysit his younger brother every day but also deal with the recent death of his dog. In contrast, Henry discovers writing helps him not to change anything but to “save everything I have.” The last scene, an open-house highlighting the children’s writing brought a lump to my throat as the parents read their child’s inner-most feelings and realize how their actions as adults and parents have unexpected and powerful effects on their children. I have to admit, Ms. Mirabel annoyed me. She dresses flamboyantly to grab attention; she is sensitive, creative, and wise in a way no ordinary teacher could ever be; and she even encourages Russell’s annoying questions that make the real teacher sigh. Perhaps I am little sensitive about the stereotype of real teachers as boring, rule-bound, and uncreative. On another note, there is something about the kids that does not ring quite true; they come across more like how an adult might romanticize that time of life rather than what real grade four kids are like. To be fair, the real author (Patricia MacLachlan) notes she visits many classrooms and receives letters from young readers of her other books, so perhaps she has a different insight into the thoughts and emotions of that age group. In fact, as she tells us in the author’s notes at the end, this book was written to address the many questions she gets about the hows and whys of being a writer in a more entertaining way. Overall, this is an inspiring book about the joys and power of writing. Recommended: 3 out of 4 starsReviewer: David SulzDavid is a librarian at the University of Alberta working mostly with scholars in Economics, Religious Studies, and Social Work. His university studies included: Library Studies, History, Elementary Education, Japanese, and Economics. On the education front, he taught various grades and subjects for several years in schools as well as museums. His interest in Japan and things Japanese stands above his other diverse interests.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.319 | 0.409 |
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".