Is Global Social Welfare Incrasing? a Critical-level Enquiry
Bibliographic record
Abstract
We assess whether global social welfare has improved in the last decades despite (or because of) the substantial increase in global population. We use for this purpose a relatively unknown but simple and attractive social evaluation approach called critical-level generalized utilitarianism (CLGU). CLGU posits that social welfare increases with population size if and only if the new lives come with a level of living standards higher than that of a critical level. Despite its attractiveness, CLGU poses a number of practical difficulties that may explain why the literature has left it largely unexplored. We address these difficulties by developing new procedures for making partial CLGU orderings. The headline result is that we can robustly conclude that world welfare has increased between 1990 and 2005 if we judge that lives with per capita yearly consumption of more than $1,248 necessarily increase social welfare; the same conclusion applies to Sub-Saharan Africa if and only if we are willing to make that same judgement for lives with any level of per capita yearly consumption above $147. Otherwise, some of the admissible CLGU functions will judge the last two decades’ increase in global population size to have lowered global social welfare.
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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 | 0.025 | 0.054 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.003 | 0.024 |
| Scholarly communication | 0.015 | 0.024 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.012 | 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".