the story circle as a practice of democratic, critical inquiry
Bibliographic record
Abstract
The authors of this essay have been committed practitioners and teachers of Philosophy for Children in a variety of educational settings, from pre-schools through university doctoral programs and in adult community and religious education programs. The promotion of critical thinking has always been a primary goal of this movement. But communal practices of critical thinking need to include other kinds of democratic conversation that prompt us to see others as full-fledged persons and to be curious about how our being in community with them makes growth and self-correction possible. As we continue to experiment and innovate in new contexts we see ourselves continuing the inquiry around expanding the inclusivity of conversations about basic human concerns. In this essay we describe an inclusive strategy called the story circle, that was first developed as a method of popular education in Denmark and was then adapted as a tool of social change among poor and dis-empowered American citizens in Appalachia. Story circles were later utilized in a philosophical living-learning community and most recently coupled with Lipman and Sharp’s dialogue method of the community of philosophical inquiry (CPI). The authors of this paper have combined story circles with the community of philosophical inquiry in a variety of contexts. In each iteration, telling one’s own story and listening carefully to the stories of others can be equally revelatory actions.
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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 | 0.048 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.017 | 0.154 |
| Scholarly communication | 0.026 | 0.023 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".