The Scarman Report, the Macpherson Report and the Media: How Newspapers Respond to Race-centred Social Policy Interventions
Bibliographic record
Abstract
This paper is concerned with tracking the shifts in media discourses surrounding issues of race and social policy interventions through an examination of the newspaper media responses to the Brixton Inquiry and Scarman Report in 1982 and the Lawrence Inquiry and Macpherson Report that appeared eighteen years later in 1999. Brought about by two very different sets of historical events, albeit events which shared certain common features, this paper argues that the Scarman and Macpherson Reports have framed the changing story of ‘race relations’ in Britain in the last quarter of the twentieth century. While there have, inevitably, been comparisons between the content of the two Reports there has not been a comparative focus on the media reception of the findings and recommendations of the Inquiries. Using written and visual media text from five newspapers the paper seeks to map the extent to which media narratives around both race and race related policy-making have shifted during the course of almost two decades. The paper questions the boundaries of any such changes and examines what remains unchanged.
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 | 0.014 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.011 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| 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".