The cost of politics: how money acts as a barrier for women in politics in the Caribbean
Bibliographic record
Abstract
This article explores the barriers to women’s political representation, focusing on financial challenges associated with political campaigns. It contributes to the emerging body of research on the gendered effects of money in politics, particularly in the Global South, by documenting the financial challenges faced by women political candidates in the Anglophone Caribbean. Data was collected through elite interviews with women politicians in Barbados, Jamaica and Trinidad and Tobago. The women were asked, among other things, to i) identify the barriers to women’s political representation and ii) recount their experiences while seeking to enter politics. Financial constraints emerged as a critical barrier to women’s political entry and participation. Although some women manage to enter the political arena and win elections, they nonetheless find the costs associated with politics burdensome and a barrier to increasing political representation for women. We conclude that, like their counterparts elsewhere, the financial demands of engaging in politics are exorbitant for women in politics in the Anglo-Caribbean due to their general exclusion from influential funding networks predominantly controlled by the “old boys’ club”; reliance on personal resources; balancing childcare and other gendered roles with demanding fundraising activities; and navigating the system of political patronage. This burden was incredibly challenging for “political neophytes” or women newcomers.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".