Comparability of<scp>GDP</scp>estimates in<scp>S</scp>ub‐<scp>S</scp>aharan<scp>A</scp>frica: The effect of Revisions in Sources and Methods Since Structural Adjustment
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
The unreliability of A frican income estimates was highlighted when G hana announced that GDP estimates were revised upwards by 60.3 percent in N ovember 2010. Similar revisions are to be expected in other countries. Many statistical offices are currently using outdated base years. It is argued that with the current uneven application of methods and poor availability of data, any ranking of countries according to GDP levels is misleading. The paper emphasizes the challenges for “data users” in light of these revisions. GDP data are disseminated through international organizations, but without any detailed data descriptions. It is argued that many statistical offices in S ub‐ S aharan A frica struggled to recover from the structural adjustment period, and the offices have not had the capacity to handle other challenges such as providing data to monitor the Millennium Development Goals. Currently, neither data users nor data producers are getting the assistance they need.
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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 | 0.017 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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