“You Never Know What Will Happen”: Youth, Affect, and the Eventfulness of Tourism Encounters
Bibliographic record
Abstract
Summary In a small town in the Caribbean region of Costa Rica, affective tourism economies shape the ways that the future is imagined and played out for racialized local youth. We tell a story of one interlocutor, Fred, a sanguine young man with a troubled childhood, to explore how intensities and emotions in his encounters with a wealthy tourist during his late teen years generated possibilities. Events unfolded to become eventfulness that made the future something. For youth like Fred, affective encounters with tourists instantiated the future, or rather, moved the future along, in indeterminate rather than predetermined or inevitable ways. Nevertheless, the hopefulness felt by Fred about the next tourist encounter that lay before him was tempered by his devaluation vis‐à‐vis a well‐off expat patrona (boss), who both stirred and deterred his dreams for “a” future.
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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 | 0.001 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".