Bibliographic record
Abstract
<JATS1:p>American education is in a funk. And it has been since the very start of the COVID19 epidemic, during the 4th quarter of the 2019-20 school year when schools across the country closed up shop or turned to what proved to be inadequate virtual learning methods. As if this weren’t alarming enough, much of the malaise that set in then has yet to dissipate. Teacher shortages, lingering and unremediated student learning loss, a lack of substitute teachers, and a dearth of applicants for para-educators and other classified employees, stubbornly persist. So how do we get back to the ‘old days’ when there was still so much joy in coming to school each day? The ancient, yet surprisingly modern, philosophy of Stoicism may hold the key, even in today’s increasingly diverse culture. By examining the underlying principles and a set of practical techniques from this philosophical school, as outlined in this book, school people—teachers, administrators, teachers’ aides and others-- may very well find a way back to happiness and tranquility in the profession they have always loved.</JATS1:p>
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".