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Record W1584247929 · doi:10.1080/14427591.2015.1045014

Situational Analysis: A Visual Analytic Approach that Unpacks the Complexity of Occupation

2015· article· en· W1584247929 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Occupational Science · 2015
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Therapy Practice and Research
Canadian institutionsWestern University
Fundersnot available
KeywordsSituational ethicsContradictionPerspective (graphical)ScholarshipSociologySituation analysisTransactional analysisOccupational sciencePsychologyEpistemologySocial psychologyComputer scienceManagementPolitical scienceOccupational therapy

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.491
GPT teacher head0.570
Teacher spread0.078 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it