Blurred Lines? Provincial Reconstruction Teams and NGO Insecurity in Afghanistan, 2010–2011
Bibliographic record
Abstract
Members of nongovernmental organizations (NGOs) have been critical of the Provincial Reconstruction Team (PRT) initiative in Afghanistan since its inception, claiming that the mixture of military and humanitarian operations has resulted in ‘blurred lines’ that inhibit insurgents from identifying who is and is not a combatant. Certain organizations have hypothesized that aid workers are more likely to come under attack as a result of this mixture. Although this claim has surfaced in multiple outlets over the years, there was a lack of empirical evidence to support it. This study tests this hypothesis using a panel-corrected standard error regression model of all 34 Afghan provinces in 2010 and 2011. Preliminary results show that NGOs were likely to encounter a greater number of security incidents in provinces with PRTs; however, further analysis reveals this was only the case in provinces with teams not led by the US. This calls into question the validity of a general ‘blurred lines’ explanation for decreased aid worker security.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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 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".