Bibliographic record
Abstract
Anthropologist Jane Briggs travelled to the Arctic in the 1960s and asked the Inuit, who at that time still lived in igloos and kept their traditions, to receive her and help her survive. She lived among them for a year and a half, and learnt their language. She observed in detail how drama is used to educate and teach children.1 When a child gets a tantrum, bites a parent, they are not scolded or punished but, rather, are shown in a playful way that involves the child what their action does to others (for example, the bite hurts the child’s mother). They are not taught in words, especially not in angry words, but by playing out the situation, sometimes by dramatically magnifying it, how they can handle their own tempers and other people. The child and their parents tell and play stories together about life, relationships and conflict resolution. Briggs was impressed by the serenity and peace of the Inuit and saw herself, in comparison, as a fierce, excessive being, and learnt a lot from them. Role playing is almost instinctive, and, just as children do it on their own without any encouragement, it was part of our human civilization even before the invention of writing: we told and played stories to each other. Role playing was made into an art by Greek drama. In the tragedy, viewers were able to encounter the topics that occupied them as well, to experience the communal, collective nature of their own history, and thus to experience ‘catharsis’ – a state of stir, exaltation, relief and spiritual purification. The Greek word catharsis means purification.
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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.016 | 0.061 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.003 | 0.024 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".