Is Violence against Union Members in Colombia Systematic and Targeted?
Bibliographic record
Abstract
Is Violence against Union Members in Colombia Systematic and Targeted?V iolence against union members and union leaders has been at the center of a debate in Colombia and in countries currently negotiating a free trade agreement (FTA) with Colombia.In particular, nongovernmental organizations (NGOs) and union leaders in Colombia, Europe, Canada, and the United States persistently argue that FTAs with Colombia should be blocked because there are no results to be seen from attempts by the current Colombian government to halt violence against union members.Furthermore, a recent report by an NGO claims that "while the Colombian government claims that most of the violence against trade unions is a by-product of the armed conflict, the Escuela Nacional Sindical (ENS), a respected NGO that provides training and support to the Colombian labor movement, says that the majority of the anti-union violence that takes place in Colombia is in response to the victims' normal union activities" (see USLEAP 2008).Union leaders, for their part, have argued that under the Uribe administration, homicides of union members have increased.For instance, in a recent letter to the permanent representatives of the EU member states, John Monks, general secretary of the European Trade Union Confederation (ETUC), argues that "assassinations of trade unionists in Colombia continue at a rate unseen in any other country. . . .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".