“Surrounded by all these contradictions”: every day culture shock in culturally diverse post-secondary classrooms
Bibliographic record
Abstract
Using a phenomenological approach, this study examined the lived experiences of students and instructors in relation to culturally diverse classrooms in an urban Canadian post-secondary institution, and what meanings they ascribed to those experiences. Data were collected through individual interviews with nine students and seven instructors, who had experienced the phenomenon. Findings revealed that first, all participants, students and instructors, were keenly aware of differences in how they personally differed and how they observed differences in those around them. Second, participants’ social location impacted how they experienced differences. Third, in their fears and hopes, participants expressed a range of emotional responses to differences. Both students and instructors seemed to have similar hopes and fears. Emotional responses were dependent upon the nature of the critical events pertaining to difference which, in turn, prompted participants to adopt strategies to deal with these events. Fourth, the discussion about cultural diversity exposed a paradox and irony between what participants said and what they actually experienced. Although participants enthusiastically attested to the richness of diversity, when looking beneath the façade, a dystopian utopia emerged where participants were “surrounded by all these contradictions.” Participants experienced a form of every day culture shock every time they entered a university classroom, and they uniformly talked about valuing difference, but practice often demonstrated the opposite. This became evident when participants talked about the pressure to fit in and about wanting to belong. Fifth, most participants evidenced varying levels of ambiguity about their personal and public identity, demonstrated in seemingly self-deprecating language. Sixth, although the traditional academic system illustrated evidence of nontraditional methods, at times the impression of openness seemed paradoxical. The distinctive nature of this study revealed that when using Freire’s critical pedagogy and Mezirow’s transformative learning as theoretical frameworks, results showed a continuum on the spectrum of power sharing with some instructors still seeing themselves as vessel fillers, to instructors on the other side of the spectrum, willing to reevaluate traditional models. Such a study is important because cross-cultural competency and sensitivity, as Street (1984) says, are essential components in today’s culturally diverse work, academic, and social environment.
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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 | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".