<i>The Essential Conversation: What Parents and Teachers Can Learn From Each Other</i> by Sara Lawrence-Lightfoot
Bibliographic record
Abstract
Not long ago a parent sheepishly recounted to me a story about receiving a letter from her son's school."I was so afraid of that letter that I didn't open it for three days!I was sure it was going to be another notification of how my son had misbehaved, but when I finally got the nerve to open it, I discovered it was good news about the great improvement he's made."Being a teacher and not a parent, this was the first time in my memory that I tuned into parents' assumptions and vulnerabilities about communications with teachers.Obviously others are more attuned to the intricacies of the relationship between parents and teachers, and the topic is important enough to warrant a fully fledged book.The Essential Conversation is that book.Harvard professor Sara Lawrence-Lightfoot focuses on parent-teacher conference interactions and suggests that anxiety is an undercurrent for both parents and teachers.In this book, Lawrence-Lightfoot elegantly and insightfully welcomes the reader to experience schooling from both sides of the desk.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.041 | 0.013 |
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".