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
Abstract I provide a summary, reflection and assessment of the current state of economic development in both the policy and academic worlds. In terms of development policy, currently, the primary focus is on policy interventions, namely, foreign aid, aimed at fixing the “deficiencies” of developing countries. Academic research also has a similar focus, except with an emphasis in rigorous evaluation of interventions to estimate causal effects. A standard set of versatile quantitative tools is used, e.g., experimental and quasi‐experimental methods, which can be easily applied in a range of settings to estimate the causal effects of policies, which are typically presumed to be similar across contexts. In this article, I take a step back and ask whether the current practices are the best that we can do. Are foreign aid and policy interventions the best options we have for poverty alleviation? What else can be done? Is our current research strategy, characterized by rigorous but a lack of context‐specific analysis, the best method of analysis? Is there a role for other research methods, for a deeper understanding of the local context and for more collaboration with local scholars?
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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