Teaching Children How to Think: Rational Autonomy as an Aim of Liberal Education
Bibliographic record
Abstract
ABSTRACT Some philosophers think that fostering children's autonomy – in the sense of critical, rational reflection on our beliefs and goals – is an appropriate aim of public educational policy. Critics say that this amounts to championing an Enlightenment outlook over ways of life rooted in faith and tradition. The most common response to the critics is to assert that children have an interest in autonomy, not because autonomy is intrinsically worthwhile, but because it is instrumentally valuable in discovering how to lead a good life. Finding fault with this Instrumental Argument, I argue that the best case for autonomy is that critical, rational reflection is something we all already rely on in everyday life to figure out which beliefs are worthy of our assent and which goals are worthy of our pursuit. The question is not whether children will reason, but whether they will reason well or poorly. Teaching children how to think critically is, thus, best understood as helping them meet their own emerging standards of rationality. And, given that we have a duty to respect others as reasoning beings, we in turn have a collective duty to foster young people's capacity to distinguish good reasoning from bad.
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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 | 0.009 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.021 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".