Safety of Journalists from a Gendered Perspective: Evidence from Female Journalists in Ghana’s Rural and Peri-Urban Media
Bibliographic record
Abstract
This study sought to explore the safety risks female journalists working in Ghana`s rural and peri-urban media encounter while doing their work, how safe they feel and how they are coping with safety breaches. Thirteen semi-structured interviews with female journalists employed by Ghanaian broadcast media outlets in rural and peri urban areas were undertaken. Guided by Braun and Clark’s (2006) six steps for qualitative data analysis, interview transcripts were thematically analysed. It was found that physical and emotional security threats; poor working conditions were the main threats to female journalists working in Ghana’s rural and peri urban media. While there are generally bad working conditions, some participants believe that men receive more benefits and opportunities for professional growth than women. Compared to their male peers, females are occasionally ridiculed and refused training and professional opportunities. When there are safety violations, employers generally offer little assistance. Female journalists cope with violations and insecurities by self-censoring, avoiding working during specific hours of the day, and steering clear of reporting conflicts, politics, and elections as a safety measure. The study recommends that to avoid maladaptive actions by journalists, media organisations address the safety needs of their female journalists. Journalists themselves should look out for personal security initiatives to enhance their skills.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".