Bibliographic record
Abstract
Purpose It is difficult to get an adequate account of human needs but there are known needs which, for hundreds of millions of people, are not met. Can the present economic system meet them? Can any economic system meet them? Is simple economic growth the answer? The purpose of this paper is to explore some of the questions, emphasizing the problems and paradoxes. Design/methodology/approach The paper looks at India where poverty is rampant despite recent gains, and at Bhutan which ranks low in economic production but quite high on the “happiness scales”. It also looks at questions of the relation of economic inequality to social problems, citing recent studies. Findings The paper focuses on how well the world's economic systems address, or fail to address, human needs. Originality/value This paper is written by a philosopher and writer on social economics (and Editor of International Journal of Social Economics (IJSE )) who works in a variety of fields: metaphysics and its epistemological relations, the theory of the history of philosophy (focusing on the seventeenth and nineteenth centuries), and moral, social, and economic philosophy and their relations to culture and religion. The paper then introduces the papers in this special issue of the IJSE devoted to human needs.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.006 | 0.014 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".