Arts and Mixed Methods Research: An Innovative Methodological Merger
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
Integrating the arts with mixed methods research (MMR) presents untapped potential for innovative methodological approaches. Arts and MMR integration exists on a continuum, ranging from low-level (e.g., communicating about MMR using art) to high-level integration (e.g., interweaving arts-based and MMR approaches), and myriad art forms are available to facilitate concept formation, data collection, analysis, and representation. Given that a primary objective of the arts and MMR respectively is to explore and understand the complex social world, arts–MMR integration has potential to enable insights not possible through the use of either approach in isolation, and to present new opportunities for transformative social change. In this article, we explore such potentials and intersections philosophically and methodologically by way of four case examples framed by the newly conceptualized Art-MMR Integration Continuum, which ranges from communicative, data source, analytic, and conceptual integration.
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 | 0.052 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.006 |
| Science and technology studies | 0.002 | 0.026 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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