Metaphysics of Presence and Difference: A Comparison of the Belief Systems Inherent in the Methodologies of Arts Based Research and A/r/tography
Bibliographic record
Abstract
Arts-integrating approaches to research are increasingly engaged in the field of education. Arts-integrating approaches offer exciting opportunities for engaging creativity and imagination in research. However, researchers should be aware that the field of arts-integrating research encompasses a number of distinct methodologies, which entail varying understandings of what constitutes knowledge. From my (arts-integrating and phenomenological) comparative inquiry into two research methodologies, arts based research and a/r/tography, I conclude that they differ in their conceptions of knowledge, and that this difference is underpinned by differing beliefs regarding the nature of reality and being. Arts based research, as elaborated by Elliot Eisner and colleague Tom Barone (Barone & Eisner, 2006; Eisner, 1991) aligns with what may be called a metaphysics of presence, while a/r/tography, as elaborated by Rita Irwin and colleagues (Irwin & de Cossan, 2004; Springgay et al., 2008) espouses what may be called a metaphysics of difference. My inquiry parses the essential elements of these contrasting belief systems through two categories that I term primacy and unity. My findings provide a useful reflection on the unavoidably paradigmatic nature of all research.
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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 | 0.032 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.004 |
| Science and technology studies | 0.008 | 0.145 |
| Scholarly communication | 0.019 | 0.025 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".