Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Beyond academic circles, there has been an expanding interest in Trinidad and Tobago, on the level of poverty in the country. Newspaper columnists and many others have joined a debate that is, unfortunately, largely based on speculation. Poverty and its measurement have always been contentious issues, more so when political contestation is imported into the debate. There has been a recent report attributed to the UNDP, which suggests a rather high level of poverty for the country, based on the use of purchasing power parities - PPP. It is not clear to this author how the PPP was generated, nor by whom. Moreover, PPPs have a limited utility and although there has been substantial work done on improving it as a tool for cross-country comparisons, there still remain difficulties that suggest that care needs to be exercised in deriving too much from it. This short paper will look at some of the data that are available and will rely on one recent study that can claim to be anchored on firm statistics and methodology in casting some light on the matter. A working hypothesis is that whatever the estimate of poverty, it is the dynamics of poverty identified in data beyond the estimate, that provide better insights into the development issues faced in attacking poverty.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it