I'm not an OT, Reflections from an Interdisciplinary Occupational Science Program through the eyes of a Geographer-Come-Occupational Scientist
Bibliographic record
Abstract
Stemming from a paper collaboratively written by the first cohort of graduate students in Canada‚s first Occupational Science program, this presentation considers two aspects of the shared vision for occupational science we developed within the context of a doctoral course ˆ interdisciplinarity and internationalization. I entered this program with a Masters of Geography and an interest in international migration, making questions of interdisciplinarity and internationalization central to my experience within this program. Working with students from different academic and cultural backgrounds offered a unique experience to consider occupational constructs within a diverse setting. This paper contributes to the vital dialogue regarding the continued evolution of occupational science by reflecting on key issues and questions related to the notion of interdisciplinarity and our connections with other disciplines. The call to be interdisciplinary has existed since the inception of occupational science, however, defining and achieving interdisciplinarity has been a struggle and some have questioned its importance. We propose that attending to questions related to the meanings of interdisciplinarity, its benefits and drawbacks, and the ways of building rich and reciprocal ties across disciplines are essential to advancing a science that aims to achieve complex understandings of occupation. The continued international growth of the discipline furthers the need for reflexivity regarding the assumptions underlying occupational research in diverse settings. Some important questions to consider include: How can we move forward in shaping an international science that does not contribute to global inequality itself, either in terms of knowledge production or within the broader political landscape? How can we build on the insights offered through the work of scholars in occupational science while avoiding a passive and wholesale import of knowledge into diverse contexts? The consideration of ontological and epistemological assumptions, the context of research, and the power of language, with respect to the dominant use of the English language within academia, are important issues relevant to this dialogue. This paper therefore emphasizes our call for continued critical reflexivity within the discipline, which involves self-reflection on how our values and academic experiences shape and are shaped by the disciplinary structures we are situated within.
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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 | 0.020 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.040 | 0.041 |
| Scholarly communication | 0.023 | 0.015 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.010 | 0.032 |
| 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".