DIMENSIONS OF RADIO COVERAGE AND CONTENT GENERATION OF AGRICULTURAL BIOTECHNOLOGY NEWS IN KENYA
Notice bibliographique
Résumé
Abstract This paper presents findings of a just concluded research designed to better understand radio usage in communicating the newly emerging field of agricultural biotechnology in Africa. While various national and international fora have acknowledged the importance of mass media in shaping perceptions and informing decision-making processes, very little has been done to gauge dimensions of coverage and the whole spectrum of content generation and capacities needed in respect to agricultural biotechnology. Quantitative and qualitative content analysis of the coverage of biotechnology issues in nine radio stations and five newspapers in Kenya over a period of one year was conducted. The articles and programmes were written or presented during a period when the country was experiencing heightened media coverage of biotechnology due to debates on enactment of a Biosafety Bill to regulate modern biotechnology. Findings revealed that agricultural biotechnology is not adequately covered by Kenyan media in a way that could enable informed public debate and policy choices. This was demonstrated by few number of items presented, little space allocated and placement of the stories in the newspapers. Radio producers cited various challenges that hindered adequate coverage of biotechnology which included: their low scientific knowledge, scientists’ use of technical jargon and unavailability of experts well versed and confident to speak in local languages. Measures should be taken to improve both quantity and quality of coverage of biotechnology issues by improving relationship between journalists and scientists. Production of a local glossary of biotechnology terms in local languages could greatly enhance confidence of radio producers and presenters. Training of journalists to increase accuracy of coverage and that of scientists on science communication skills cannot be overemphasised. Key Words: Agri-Biotechnology, Radio, GMOs, Communication, Mass Media Acknowledgment This research was supported by the International Development Research Center (IDRC) of Canada JCMRJournal of Communication and Media Research, Vol. 3, No. 2, October 2011, 13 – 27. © Delmas Communications Ltd. About the authors *Dr. Margaret Karembu and Faith Nguthi are with the International Service for the Acquisition of Agri-Biotech Application (ISAAA Africenter), Nairobi, Kenya. **Toepista Nabusoba is with the Kenya Broadcasting Corporation, Nairobi, Kenya. ***Peter Oriare is with the University of Nairobi’s School of Journalism and Mass Communications, Nairobi, Kenya. ****Julius Nyangaga is with the International Livestock Research Institute. *****Heidi Schaeffer is with Rhythm Communications, Canada. ******Mary Myers is a Development Communication Consultant in the United Kingdom. Full Article Words: 6,349; Pages: 15
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».