Death in Gambella: What Many Heard, What One Blogger Saw, and Why the Professional News Media Ignored it
Bibliographic record
Abstract
Doug McGill published several articles about the massacre of 425 members of the Anuak tribe by the Ethiopian military in 2003 and 2004 on his Web site, The McGill Report. The mainstream news media ignored it. McGill's narrative demonstrates the impact of his reporting on the Anuak community worldwide, its impact on several beneficiary groups in the United States, and the lack of interest by the mainstream news media that failed to fulfill journalism's primary purpose. Two responses follow McGill's narrative. Jeremy Iggers examines the social and economic realities that make it difficult for journalists to fulfill their primary purpose. He suggests that partnerships between journalists and engaged citizens may provide a new model for journalism. Andrew Cline examines the rhetorical and ethical nature of the journalistic transaction between journalist and audience. Who counts as a journalist arises from the experiences of an audience that uses a journalist's work as a civically important text.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.006 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".