‘Newsworthy victims’: The killing of Maxwell Mahama and the culture of lynching in Ghana
Bibliographic record
Abstract
Following the 2017 killing of Maxwell Adam Mahama by a lynch mob in Ghana, this article engages with the subject of lynching in Ghana through a content analysis of newsmedia items relating to the practice. While reactions to Mahama’s killing invite optimism that lynching as a form of instant (in)justice is being problematized in Ghana, this study leads to a less optimistic position. State, media and public responses to Mahama’s killing were compared vis-à-vis similar killings of two police officers – Jerry Wornoo and Richard Owusu-Sekyere – in 1998. Drawing on the relevant literature, this study concluded that a number of factors combined to make Mahama, Wornoo and Owusu-Sekyere ‘newsworthy victims’. In contrast, victims in several lynching cases reported by Ghanaian media between 1999 and May 2017 were not deemed newsworthy, thus attracting less attention. Consequently, there have been missed opportunities following the Wornoo and Owusu-Sekyere killings to make critical systemic interventions in Ghana to prevent lynching. Hence, it is argued, the mere sensationalization of Mahama’s lynching may not trigger the requisite systemic social change. Recommendations are made to harness the momentum from Mahama’s killing to address instant (in)justice.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".