Guatemalan Ex-Combatant Perspectives on Reintegration: A Grounded Theory
Bibliographic record
Abstract
While reintegration programs for ex‐combatants have become a major focus of cease fire agreements, their success remains elusive. In this study, I interview members of Nuevo Horizonte, an intentional community comprised of Guatemalan ex‐guerrillas. These men and women reflect on two questions: what was reintegration like, and what advice do you have for other reintegrating ex-combatants. Using a grounded theory approach, common themes (such as being united) were developed and lead to a substantive theory of their transformative reintegration process. The collective voice of these ex‐ combatants challenges conventional reintegration programs by (a) challenging the demobilization prerogative showcasing how their unity was integral to their reintegration experience and (b) challenging the development model in which ex‐combatants are viewed as lacking capacity and in need of outside experts to deliver solutions. By highlighting how reliance on their own capacity resulted in their successful reintegration, these ex‐combatants believe their experience can assist other ex‐combatants around the world.
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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 | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.027 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".