Situational Analysis: A Visual Analytic Approach that Unpacks the Complexity of Occupation
Bibliographic record
Abstract
Concurrent with the development of a transactional perspective, the notion of “the situation” has increasingly been taken up in occupational science scholarship. Accordingly, research methodologies and approaches that capture the multifaceted elements of situations need to be explored. Situational analysis, pioneered by sociologist and grounded theorist Adele Clarke, shows promise for facilitating inquiries into situations of occupational engagement. In this article we review the situational analysis approach and provide an example of its application to research on the situation of long-term unemployment. In this application, situational mapping illuminated the contradiction of simultaneously being “activated” and “stuck”. Situational analysis helped unpack how this contradiction was shaped within North American contexts. Based on this example and others outside the occupational science literature, we discuss how situational analysis can be a useful tool for fostering critical, socially-responsive, and community-engaged occupational science 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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.005 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".