Phenomenological Research Needs to be Renewed: Time to Integrate Enactivism as a Flexible Resource
Bibliographic record
Abstract
Qualitative research approaches under the umbrella of phenomenology are becoming overly prescriptive and dogmatic (e.g., excessive and unnecessary focus on the epoché and reduction). There is a need for phenomenology (as a qualitative research approach) to be renewed and refreshed with opportunities for methodological flexibility. In this process paper, we offer one way this could be achieved. We provide an overview of the emerging paradigm of post-cognitivism and the aligned movement of enactivism which has roots in phenomenology and embodied cognition. We argue that enactivism can be used as a flexible resource by qualitative researchers exploring the unfolding of first-person (subjective) experience and its meanings (i.e., the enactive concept of sense-making). Enactive approaches are commonly tethered to “E-based” theory, such as the idea that sense-making is a 5E process (Embodied, Embedded, Enacted, Emotive, and Extended). We suggest that enactivism and E-based theory can inform phenomenological research in eclectic and non-prescriptive ways, including integration with existing methods such as observation/interviews and thematic analysis with hybrid deductive-inductive coding. Enactivism-informed phenomenological research moves beyond methodological individualism and can inform novel qualitative research exploring the complex, dynamic, and context-sensitive nature of sense-making. We draw from our enactive study that explored the co-construction of pain-related meanings between clinicians and patients, while also offering other ways that enactive theory could be applied. We provide a sample interview guide and codebook, as well as key components of rigor to consider when designing, conducting, and reporting a trustworthy phenomenological study using enactive theory.
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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 | 0.267 | 0.279 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.015 | 0.066 |
| Scholarly communication | 0.026 | 0.074 |
| Open science | 0.006 | 0.023 |
| Research integrity | 0.010 | 0.025 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".