Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Critical thinking instructors are faced with an overwhelming number of textbooks to choose from for their courses. Many of these texts do not reflect an awareness of current scholarship in critical thinking and informal logic. I argue that instructors should only adopt textbooks that reflect a sound theoretical understanding of the topic by acknowledging the central role of critical thinking dispositions, offering a more nuanced approach to the teaching of fallacies and of inference, stressing dialectic and argument revision, focusing on the analysis and evaluation of real arguments, and broadening the scope of critical thinking beyond argument analysis and evaluation. To support instructors in this regard, I critique one popular textbook now in its sixth edition that does not satisfy many of these criteria, Munson and Black (2012), and applaud one new textbook that I find does succeed on many of these fronts, Bailin and Battersby (2010).
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.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it