Contradictory socio‐economic consequences of structural adjustment in Kingston, Jamaica
Bibliographic record
Abstract
Since the early 1980s, the introduction of International Monetary Fund‐directed structural adjustment packages to stabilize the Jamaican economy has reduced the scope of the government, cut back its capacity to intervene in the housing market, opened the economy to foreign goods (but limited capital), and re‐produced the colonial version of a non‐dynamic, labour‐surplus urban economy in Kingston. This paper traces the impact of structural adjustment on unemployment and class formation in Kingston, and the relationship of these issues to housing problems. Rented, poor‐quality housing, underpinned by low socio‐economic status and historically high rates of unemployment, has created an overt spatial concentration of poverty, located in West and East Kingston. Nevertheless, overall unemployment is currently lower than at independence in 1962, and virtually all housing indicators have recorded improvements over the same time period. These improvements have been due to a deceleration in the growth of Kingston's population since the mid‐1960s; government commitment, despite structural adjustment, to improve the quality of collective consumption; and the determination of Kingston's citizens to build better homes for themselves, often aided by loans from local building societies and remittances from family members resident overseas. However, at least a quarter of Kingston's population remains both unemployed and concentrated into areas of poor quality housing. These circumstances in Kingston are compared with those in adjacent Latin American cites under structural adjustment.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".