Contrasting Socio-Economic and Demographic Profiles of Two, Small Island, Economic Species: MIRAB versus PROFIT/SITE
Bibliographic record
Abstract
The MIRAB model developed by Bertram and Watters, based on remittances and aid, has dominated the small island economy literature for two decades. Recently, two challenges have surfaced: the PROFIT formulation emphasizing domestic policy flexibility - a socalled ‘resourcefulness of jurisdiction’ - and a dynamic private sector (Baldacchino, 2006); and the SITE model, stressing the role of tourism (McElroy, 2006). To date, there has been no comparative assessment of these different island models. This article addresses this gap. Its point of departure is to consider SITE islands as a subspecies of the PROFIT cluster. It constructs comprehensive profiles across 27 socio-economic and demographic variables for two island sub-groups with populations of less than three million: 23 MIRAB and 35 PROFIT-SITE. Results indicate PROFIT-SITE islands are much more affluent, socially advanced and demographically mature than their MIRAB counterparts.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".