1 Victims navigating justice in island communities: An exploration of victims’ experiences of the criminal justice system and quality of justice services provided in Trinidad and Tobago
Bibliographic record
Abstract
The criminal justice system in Trinidad and Tobago, like other Anglophone Caribbean islands, is a remnant of its colonial past. While there have been some reforms to improve the quality and type of police and justice services provided, the issues justice users encounter in their access and engagement remain underexplored. Using interview data from direct and indirect victims, this paper explores the complexities of victims’ experiences and their implications on the quality and type of police and justice services provided. Victims’ narratives expressed varied experiences in interpersonal treatment, information services, input and engagement, and effectiveness and efficiency of the process. Many were required to navigate interpersonal, structural, and systemic barriers which led to institutionalized secondary victimization, as well as feelings of silencing and inequality. The findings suggest that victims’ experiences were influenced by the legacies of colonialism which continue to persist in island communities. Such as, imbalances in power, behaviours within institutions that promote solidarity networks, negotiation, informal systems, and processes. The narratives of victims intimate that there is a need for change and the adoption of an approach that not only improves the quality of justice services provided but empowers victims through the process.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".