Bibliographic record
Abstract
Purpose Academics examining the global South who engage in informal politics to understand social and political issues should be prepared to diversify their methods toolkit. Informal ties and politics are where one learns about social and economic exclusion. The paper aims to discuss these issues. Design/methodology/approach Mixed qualitative methods – such as individual interviews, surveys, and focus groups – provide an understanding of the people’s perspective, enabling the researcher to truly know what is going on. Findings Fieldwork in the downtown communities of Kingston, Jamaica, has an element of danger because violence and politics are very much a part of the daily reality of the people being interviewed. In this paper, the author argues that studying how financial resources are allocated to low-income people and understanding why some groups purposefully self-exclude themselves from economic development programs require unorthodox field methods. The author thus uses political ethnography to understand the experience of marginalized Jamaican people. Originality/value Mixed qualitative methods and political ethnography assisted the author to understand the actual experience of marginalized people and politicized financial programs.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".