Auto-Bio/Ethnography as a Curriculum in Cross-Culture Communication: A Voice from the Other Shore
Bibliographic record
Abstract
In an increasingly globalized and multicultural world, authentic auto-bio/ethnographic travel accounts have become representations of the social, cultural, historical, and political intricacies in cross-culture communication. In this research study, I critically analyze three excerpts from my diary narrated in the form of short stories in order to answer two research questions: How do cultures shape our personalities? And, what factors influence cross-culture communication of the “Self” and the “Other?” I selected the Thematic Analysis method in Narrative Analysis to analyze my three narratives. The narrative analysis resulted in three themes: cultural identities, appearance and reality, and bridging the gaps. I argue that being an Arab, Muslim, female with hijab (hair scarf) in the U.S. after 9/11 creates a complex experience in cross-culture communication. I conclude that international students’ auto-bio/ethnography travel accounts can be implemented as a curriculum to celebrate our similarities and respect and appreciate our differences. Key words: Auto-bio/ethnography; Curriculum; Self actualization; Cultural agent; Hijab
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.021 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".