Bibliographic record
Abstract
Critical thinking deserves both imaginative teaching and serious theoretical attention. Studies in Critical Thinking assembles an all-star cast to serve both.EDITOR: J. Anthony Blair (Windsor) INTRO: On What Critical Thinking Is (Alec Fisher, East Anglia) PART II On Teaching CT (Blair & Scriven) 5 Exercises: Validity (Derek Allen, Toronto), Teaching Argument Construction (Kingsbury, Waikato), C.T About Students’ Own Beliefs (Tracy Bowell, Waikato & Justine Kingsbury), Settling Conflict by Compromise (Jan Albert van Laar, Groningen), Using Arguments to Inquire (Sharon Bailin, Simon Fraser & Mark Battersby, Capilano) PART III 7 Chapters on Argument: Arguments and CT (J. Anthony Blair), The Concept of an Argument (David Hitchcock, McMaster), Using Computer Aided Argument Mapping to Teach CT (Martin Davies, Ashley Barnett, Tim van Gelder, Melbourne), Argument Schemes and Argument Mining (Douglas Walton, Windsor), Constructing Effective Arguments (Beth Innocenti, Kansas), Judging Arguments (Blair), Introduction to Fallaciousness (Christopher Tindale, Windsor). PART IV 7 Chapters on Useful Background for CT: How a Critical Thinkeer Uses the Web (Sally Jackson, Illinois at Urbana-Champaign), Definition (Robert Ennis, Illinois at Urbana-Champaign), Generalizing (Dale Hample & Yiwen Dai, Maryland), Appeals to Authorit8y: Sources & Experts (Mark Battersby), Logic and CT, (G.C. Goddu, Richmond), Abduction and Inference to the Best Explanation (John Woods, British Columbia). The Unruly Logic of Evaluation (Michael Scriven, Claremont)
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 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 | 0.015 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.005 | 0.026 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".