Editors’ introduction to the series
Bibliographic record
Abstract
This book provides the first detailed examination of the practice of policy analysis in Mexico. It studies how public institutions and other non-state actors gather and review information and ponder options in the process of making (or trying to influence) policy decisions. Its chapters also offer explanations that are helpful for understanding how and why policy analysis activities vary across settings, and why this intellectual activity has made significant progress but is still far from being fully established in the country. While these are questions that have great theoretical and practical relevance, they had remained rather under-researched until now. The book follows a similar structure to that of other volumes in the International Library of Policy Analysis of the Policy Press. It thus seeks the double objective of telling the intellectual story of Policy Analysis in Mexico, as well as of giving a detailed account of policy analysis as a practical endeavor in the country. Moreover, the book describes how policy analysis takes place in a variety of state institutions and a number of non-state organizations which are permanently and directly involved in public affairs. The comprehensive view that results from this effort should thus be of interest to those who are keen to learn more about policy analysis and policy making in Mexico, and to those who favor comparative policy studies but cannot always access relevant information on developing nations.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.219 | 0.103 |
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".