Bibliographic record
Abstract
Social justice is a contested concept. For example, some on the left argue for equality of outcomes, those on the right for equality of opportunities, and there are differing emphases on the roles of state, market and individual in achieving a socially just society. These differences in emphasis are critical when it comes to examining the impact that public policy has on minority ethnic groups. Social justice should not be culture-blind any more than it can be gender-blind yet the overwhelming burden of evidence from the UK shows that public policy, despite the political rhetoric of fifty years of governments since large-scale immigration started, has failed to deliver social justice to Britain’s minorities. In terms of outcomes, in respect for and recognition of diversity and difference, in their treatment, and in the failure of governments to offer an effective voice to minorities, the latter continue to be marginalised in British social, economic and political life. This is not an argument for abandoning the project of multiculturalism, however, but for ensuring that it is framed within the values of social justice.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.026 | 0.013 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.004 | 0.005 |
| 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".