Arts-based Methods in Socially Engaged Research Practice: A Classification Framework
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Arts-based research has recently gained an increasing popularity within qualitative inquiry. It is applied in various disciplines, including health, psychology, education, and anthropology. Arts-based research uses artistic forms and expressions to explore, understand, represent, and even challenge human experiences. In this paper we aim to create order in the messy field of artistically inspired methods of socially engaged research. We review literature to establish study and distinguished three major categories for classifying arts-based research: research about art, art as research, and art in research. We further identify five main forms of arts-based research: visual art, sound art, literary art, performing art, and new media. Relevant examples of socially engaged research are provided to illustrate how different artistic methods are used within the forms identified. This classification framework provides artists and researchers a general introduction to arts-based research and helps them to better position themselves and their projects in a field in full development.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.290 | 0.178 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.019 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.000 | 0.013 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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 it