Generative exhaustions: Thresholds of long-term uncertainty and stink bug infestation in Georgia’s contested borderland
Bibliographic record
Abstract
Displaced Georgians from the Gali region of the de facto Georgia–Abkhazia borderland have constructed mobile lives by navigating a decades-long conflict and its turbulent landscapes. For the people of Gali, cross-border mobility is a vital concern; uncertainty is a daily matter of tactical anticipation. Arbitrary checkpoints, unannounced border closures, and the Enguri River’s capricious water levels interfere with mobilities; occasional crises unsettle the subtle ways that the Gali people have developed over three decades to manoeuvre everyday uncertainties. Focusing on an unanticipated stink bug infestation that disrupted already precarious lives, this article explores the temporal and affective anatomy of long-term uncertainty with its continuities and limit points. Using exhaustion as an analytical concept, it examines the generative thresholds of protracted uncertainty without eclipsing the cumulative toll of continuous life struggle in a conflict zone.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".