Foreword
Bibliographic record
Abstract
The globalization process constantly spawns new ideas, and researchers are generally willing to share and adapt them. It can be recalled that UNDP report no. 1/1990 saw the basic objective of human development as the enlargement of the range of people’s choices, which are not fixed forever. There have been many approaches to the study of human development. For instance, Classical Economics measures human development using the size of a country’s GDP or per capita income. The Welfare Approach uses income and consumption. The Utilitarian Approach focuses on happiness, good and pleasure, while the Basic Needs Approach measures access to water, shelter, food and sanitation, among others. It is impressive that, just ten years later, Amartya Sen managed to pull all these ideas together into a single framework called the Capability Approach. This new concept of measuring human development focuses on freedom as development. Although nowadays widely known, the Capability Approach is still rarely used in population studies and policies, and this is especially true for Africa. This volume is therefore welcome, but in addition it is timely, and this for at least two reasons.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.528 | 0.494 |
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".