Voting for Security. A study on security as an electoral priority in Colombia’s capital Bogotá during the presidential elections of 2010.
Bibliographic record
Abstract
In this thesis I will present a study on security as an electoral priority during the presidential elections of 2010 in Colombia. For this, I conducted four months of fieldwork in poor and wealthy neighbourhoods in Colombia’s capital Bogotá. Colombia is a particular country; excessive violence goes hand in hand with a relatively stable democracy. Since security is a basic need for people, it plays an important role during elections. People who live in fear because of violence are generally willing to pay a high price for security, which can include restrictions on democracy and human rights violations. Under President Uribe, who came to power in 2002, the perception of security has changed for many Colombians thanks to his hard-line security policy against guerrilla movement FARC. In this thesis I will analyze to what extent the perception of security has changed, and whether this has led to a change of electoral priorities for the voters in a time when Uribe has to leave office. I argue that the perception of security influences electoral priorities and preference for a candidate.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".