What’s Wrong With Our Schools and How We Can Fix Them, by Michael C. Zwaagstra, Rodney A. Clifton, & John C. Long
Bibliographic record
Abstract
I most often approach books offering "fixes" with a certain measure of caution.I base this on the fact that, from my experience such books often address the complex topic(s) raised by the author(s) from a relatively limited or superficial perspective.Sadly, my sense of caution was validated as I engaged with What's Wrong With Our Schools and How We Can Fix Them.To position myself in relation to the topics the book examines, I should say that I have been a public school teacher and administrator for the past 23 years.I have taught all grades from K-12, and adults in vocational, college, and university streams in a variety of settings.My post-graduate research examined the principalship and schools in northern Canadian and Indigenous contexts.It is from this multiplicity of perspectives that I offer the following observations on this book. About the bookThe philosophical approach of the book is as follows: (a) traditional methods in public education are good, and (b) efforts to stray from them are misguided."Romantic progressive" approaches to education are unwise and should be avoided or abandoned if already subscribed to.In presenting their perspective, the authors rely heavily on E.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".