Immersion In Another Culture: Paradoxical Experiences Considered For Teachers And Students In University Classrooms
Bibliographic record
Abstract
We have worked, learned, and lived in Indonesia. These experiences prompted Roger’s PhD dissertation entitled: Expatriate Managers’ Immersion in Another Culture: A Phenomenological Study of Lived Experiences. The findings of this research uncovered eight paradoxical experiences that were lived by persons who were immersed in another culture. We have shared these paradoxes with others and have found that they, too, have experienced similar situations and feelings. We believe that these paradoxes are universal and could be viewed from the perspective of teachers in university classrooms and their students, each of whom may or may not “come from away”. By taking the opportunity to illustrate these paradoxes from individuals’ perspectives in this paper, understanding will ensue about what it is like to be immersed in another culture, thus transcending understanding -- to seeing the phenomenon (being immersed in another culture) in a new light. This insight will assist teachers and students from different cultures to feel understood and supported in classrooms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".