Inequality and social harm: Revisiting the Spirit Level debate by reproducing and updating it, as well as reanalysing the data with qualitative comparative analysis
Bibliographic record
Abstract
This article explores the relationship between inequality and social harm, revisiting the original “Spirit Level” data from Wilkinson and Pickett, updating it for a later time period, and considering what difference it makes to their results by addressing criticisms made of their original research by using an alternative measure of inequality and expanding the range of possible causal factors. To achieve this, it makes use of both the original method used by Wilkinson and Pickett and that of a different approach, Qualitative Comparative Analysis. It finds that a measure of the kind of democracy (lower “integrative democracy”), along with higher inequality, are the key factors at the root of solutions for explaining higher social harm in both periods, which both follow up the suggestions by Wilkinson and Pickett about the role of democracy in explaining social problems, as well as making the extent and means of that relationship clearer.
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 | 0.065 | 0.115 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.008 | 0.055 |
| Scholarly communication | 0.013 | 0.024 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".