Natalie Alvarez, <i>Immersions in Cultural Difference: Tourism, War, Performance</i>
Bibliographic record
Abstract
This book documents cultural encounters facilitated in immersive role-play scenarios of military and counterinsurgency training, dark tourism, and pedagogy based on history, topography, and the politics of human rights violations. Among the four case studies, two concern training for North American combatants engaged in declared and covert wars in the Middle East; two feature Indigenous cultures claiming control over their narratives, designed to proactively alter a people’s future; and whereas one relies on a built simulation three others utilize the natural landscape to shape encounters. Like studies by Scott Magelssen and Coco Fusco, among others, Natalie Alvarez’s work is invested in formal characteristics of the cases, such as live immersive situations, for paradigm-building. Yet, more importantly, it is cultural ethnography that first destabilizes then reorients the ethnographer’s understanding of kinds of knowledge and leads to sensitization to local cultures and ethical experiences of learning. It matters less whether the cases cohere in terms of formal elements of performance than that, through field work and ethnographic reflection, performance is indispensable in promoting personal encounters imbued with empathy. Over the course of many years, Alvarez’s field work—at CFB Camp Wainwright’s Afghan Village training site, the private company Aeneas Group International’s course on Countering Insurgency in Complex Environments held in the Utah mountains, a nighttime walk led by Indigenous Hñahñu in Hildalgo northeast of Mexico City simulating perils encountered by border-crossing migrants, and a tour of Shoal Lake 40 Reserve conducted by a community leader and settler-ally through this Anishinaabe reserve in southeastern Manitoba—accumulates into a profound meditation on experiences of encounter.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".