Values Reasoning for Critical Thinking: Completing the Process
Bibliographic record
Abstract
Values reasoning is a multidimensional process designed to help students assess value questions or claims, make defensible judgements about issues and resolve value conflicts. This overall process and sub-processes help students develop critical ways of thinking and dispositions to make wise and effective decisions in different contexts and subject areas. Several sub-processes of values reasoning introduced at the 2005 AAU Teaching Showcase will be reviewed briefly and the remaining subprocesses will be introduced. These include pairing value principles with factual claims, identifying points of view and testing a value judgement with the Universal Consequences and Subsumption Tests. The contribution of these additional sub-processes to critical thinking will be explored
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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 | 0.083 | 0.124 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.010 | 0.024 |
| Scholarly communication | 0.025 | 0.025 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.013 | 0.007 |
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".