Exotic Place, White Space: Racialized Volunteer Spaces in Honduras
Bibliographic record
Abstract
In every year between 2004 and 2012, more than 800,000 Americans reported volunteering internationally (Lough ). These volunteers are overwhelmingly white (McBride and Lough ) and entering a largely nonwhite and developing world. This study starts by questioning how racial status informs volunteer/volunteer tourist interactions, both with locals and with other volunteers, in a global context. In‐depth interviews with 23 missionaries, teachers, and volunteers from the United States and Canada reveal that (1) international volunteering is largely motivated by romantic and exotic understandings of the Global South and (2) in spite of a stated interest in cultural immersion, participants’ notions of their whiteness guided their perceptions of Hondurans and their actions as they sought out and retreated to white spaces protected from Honduran influence. These findings further the work of those who have argued first world travelers have homogenized spaces on reserve, by demonstrating that whiteness can be the basis for the construction and maintenance of protected spaces in predominantly nonwhite countries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| 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".