Bibliographic record
Abstract
Over and over in my life, I have personally experienced the power of the arts to inspire, endear, provoke, and challenge my interpretations, memories, and perceptions.As an arts educator, one of my most profound experiences was witnessing the need of others to create as they inquired into educational issues.Of course, I knew this for myself.I recalled as a teenager, interpreting a high school biology assignment artistically, taking up the ethical debates of science in a collage resembling a stained-glass church window.How could I portray the depth and breadth of unanswerable problems?Storying the issues visually, in an outline quickly understood, drew viewers into the particularities of abiding scientific and ethical or moral dilemmas.It may not have illustrated a definitive answer, yet it certainly raised the issues in accessible, evocative, and meaningful ways.I was also struck by my biology teacher's reaction.No one else had offered a creative response and yet, the response created a focus for the class discussion, bringing to life the very essence of the issues we were studying.An artistic response brought the issues to life.As an arts educator, I have learned that many people need to engage with the arts in order to make their thinking visible, to hear the sounds of their inquiries, to perform the embodied nature of their ideas, or to story their experiences.For some, this is essential work unto itself.The processes of engagement through the senses teaches us something we can only learn through our senses.In this way, the arts not only act as a guide for inquiry, they become the basis for how one's work is shared.Over the last three or more decades, an interesting confluence has emerged between artistic forms of inquiry, and those of action research or participatory action research.While the latter may not imply artistic forms of engagement, for some individuals, myself included, they had a natural affinity, especially if action research embraced living inquiry rather than a step-by-step progression (McNiff & Whitehead, 2012).Although I studied action research in my own graduate work, it wasn't until I was teaching in a graduate
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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 | 0.220 | 0.184 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.011 | 0.007 |
| Science and technology studies | 0.027 | 0.184 |
| Scholarly communication | 0.062 | 0.073 |
| Open science | 0.008 | 0.045 |
| Research integrity | 0.025 | 0.040 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".