Navigating between Scylla and Charybdis: SoTL as its Own Kind of Inquiry
Bibliographic record
Abstract
Although there is ample literature that explores what SoTL is and offers guidelines on how to do SoTL, we have not paid enough attention to the fundamental assumptions that underpin systematic scholarly inquiry itself, regardless of the context or the object of study. Instead, we seem to have a narrative that relates SoTL to the disciplines and/or educational research. In this paper, I challenge this narrative with the help of philosophy of science. Specifically, I argue that SoTL is at risk of being appropriated by disciplinary paradigms. This means we would do well to adjust how we conceptualize SoTL. To find a better way, I use Habermas’ concept of knowledge-constitutive interests to argue that we should start by recognizing the fundamental interests at play when we do SoTL, regardless of disciplinary context. I connect Habermas’ three interests (instrumental, interpretive, and emancipatory) to Hutchings’ taxonomy of SoTL questions (what works? what is? and what could be?) and to three basic paradigms of inquiry (normative, interpretive, and critical realist). These connections show how philosophy of science in the form of Habermas’ critical theory can combine with existing conceptual literature on SoTL and established paradigms of inquiry that exist independently of the disciplines. I aim to show that we can use philosophy of science to conceptualize SoTL in a way that allows it to stand fully on its own merits, as its own form of inquiry, with disciplinary perspectives only influencing it in appropriate and useful ways.
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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 | 0.029 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.014 | 0.131 |
| Scholarly communication | 0.022 | 0.032 |
| Open science | 0.003 | 0.017 |
| Research integrity | 0.008 | 0.016 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".