Bibliographic record
Abstract
Slow Reading by John Miedema. Duluth, MN: Litwin Books, 2009. 92pp. ISBN 978-0-9802004-4-7. Fast! The speed of life seems to rule our world today. Fast food, fast cars, fast connections, instant communication, instant gratification…time races forward, technology races forward, and we race to keep up. Social commentators, psychologists, and educators decry the cost of the sped-up world on our abilities to focus and perform tasks that require time and concentration. Nicholas Carr (2008) describes his own experiences in his article “Is Google Making Us Stupid?”: I’m not thinking the way I used to think. I can feel it most strongly when I’m reading. Immersing myself in a book or lengthy article used to be easy…That’s rarely the case anymore. Now my concentration often starts to drift after two or three pages. I get fidgety, lose the thread, begin looking for something else to do. I feel as if I’m always dragging my wayward brain back to the text. The deep reading that used to come naturally has become a struggle. Several movements are now questioning the wisdom of life in a constant fast lane, proposing alternatives that bring satisfaction at a slower pace. Groups advocating slow food, slow travel, slow parenting, slow sex, slow art, and other slow movement activities champion the benefits of more deliberation and reflection in our everyday lives. In his book Slow Reading, author John Miedema presents the title concept as a spectrum of voluntary actions that readers of all levels and tastes can use to increase their pleasure and comprehension, while examining its development and numerous facets. Slow Reading contains only sixty-five pages of text, but it is packed with discussions and references that support the author’s goal of providing “a first, full sketch of the breadth of the subject of slow reading, encouraging further research in the area, and inspiring readers to take up slow reading for pleasure” (p. 5). The detailed index affords quick access to specific points in the discussions, and an eleven page bibliography provides an exhaustive list for further investigation into the topic and its related fields. Miedema began researching the concept of slow reading while a student in the Library and Information Science program at the University of Western Ontario, and this book developed out of his master’s thesis. The discussions in each chapter are brief, but offer plenty of food for thought for educators, librarians, pedagogical researchers, and others interested in the impact of technology on the act and future of reading. The five chapters of the book consist of four essays exploring the topic from different perspectives and disciplines and a summary of ideas for the implementation of slow reading. Miedema emphasizes that “Slow reading is not about reading as slow as possible at all times, but rather exercising the right to
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.080 | 0.083 |
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".