‘Don't make my people beggars’: a developing world house of cards
Bibliographic record
Abstract
Recent years have seen increasing participation in short-term international volunteering. These volunteer teams usually engage individuals from high-income countries to travel and provide charitable services for host communities in low- and middle-income countries for a period of 3 months or less. The economic impacts arising from this phenomenon often vary; while volunteers introduce a new revenue that may support local job creation, they may also inadvertently disrupt the local workforce with their contributions, and thereby drive up unemployment. In addition, there may be a shift of economic focus towards attracting and supporting volunteers, rather than developing meaningful capacity in needed developmental areas. There also exist expected tensions with the direct and indirect goals and impacts of visiting volunteer teams, such as intended evangelism, unintended cultural colonialism, or education over service. Weighed against the desirability of additional community revenue, these tensions raise numerous ethical concerns. This paper examines a medium-sized city in Latin America, which receives many well-meaning international volunteers annually, who serve disadvantaged local populations. Specifically, this paper examines a faith-based volunteer team that was primarily composed of non-skilled youth. Using participant observation and interviews with relevant stakeholders, we identified an unsustainable growth model in place at the local hospital, which directs resources to support and promote the flow of foreign volunteers despite ethical concerns around perpetuating poverty, skills mismatch, and limited beneficial impacts on the target population. We highlight future concerns for this community associated with a financial dependence on international volunteers, and present solutions to potentially mitigate this issue.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.028 | 0.008 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.018 | 0.002 |
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".