Shaping knowledge regarding occupation: Examining the cultural underpinnings of the evolving concept of occupational identity
Bibliographic record
Abstract
BACKGROUND/AIM: Within occupational therapy and occupational science, knowledge regarding occupation-based concepts is in the process of being developed, disseminated and acted upon internationally. It is critical to reflect on the forces shaping the ways in which this knowledge is being constructed. METHOD: In this paper, the ways in which cultural assumptions and values have influenced the evolving concept of occupational identity are examined through applying Kluckhohn and Strodtbeck's framework of cultural variations in values to two contemporary conceptualisations of occupational identity. RESULTS: The analysis demonstrates the ways in which values most consistent with Western culture are embedded within and dominate these contemporary conceptualisations of occupational identity, emphasising a future orientation, achievement-based doing, individual choice, and mastery of individuals over nature. CONCLUSIONS: This paper points to conceptual boundaries within which occupational identity is currently being shaped and points to alternative possibilities in the hope of prompting dialogue and research that looks at this concept in more diverse ways. Heightened sensitivity to the influence of culture on the shaping of occupation-focussed knowledge will serve to strengthen and enrich the growth of the evolving body of knowledge pertaining to occupation, and foster culturally sensitive research and practice.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".