Bibliographic record
Abstract
Reflections on research can take many forms. They inevitably contain positive memories of research that advanced our knowledge on issues of the day. They can also reflect dead ends and disappointments. Although research in rural development is generally a public endeavor (government, university and NGO supported projects), the effects felt by the researcher are often personal. Meeting peasants in the field, listening to abused farm women, and tracing livelihood transitions are all challenging for the researcher. Above all, making sense of research results for policy development is a daunting task, as there are many layers of dilution and deflection between researcher and policy maker. With these impediments and opportunities in mind, I offer some of my own reflections, in the form of an opinion piece, on rural development research over the past 50 years. The paper is organized into three parts: macro and micro level observations about the evolution and prevailing trends in rural development, and a third section on contemporary and future issues.
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.
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 | 0.018 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.006 | 0.016 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".