Bibliographic record
Abstract
In this paper I take an historical look at dance artists and theorists, examining their influence on today’s curriculum in our school system. I argue that dance education should be recognized as of equal importance as other art forms, that it is essential for our society’s well being, and that it should be included and fostered in our school curricula. I further examine a number of key contributors to dance and dance education within the last century in the Western sphere. Key questions I examine are: Who were some of the most influential dance artists and dance educators of the past century? Who were the innovators and key contributors? How has their work affected dance education? How has their work been passed on? Have their bodies of work, their methodologies, or their beliefs about the body changed society? Has their work shaped culture or was it a byproduct or reflection of culture and the forces of the time they lived? As well as an historical look at dance artists and theorists, I also undertake a philosophical inquiry, examining the idea of dance in the curriculum as being misunderstood: as an area to explore feeling, but not intellect. Finally, I look at the essentialness of an integrated dance and movement education as a way of connecting human beings to their bodies, as well as using the body as an essential means of expression.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".