Citizen videojournalism in professional online news media as a vehicle for democracy
Notice bibliographique
Résumé
"Citizen journalists have reconstructed the traditional means of journalism practice by being their own eyewitness reporters, producers, and news information distributors; they self-advocate for citizens' voices, analyze news, debate, and construct news stories from citizens' perspectives. The internet has created an open system that encourages free press and enables the mobilization of the rights and practice of public free speech. Deliberative democratic goals are significant in participatory journalism, and these challenges mainstream news journalism in their traditional roles as conveyors of journalism standards, professional practices, and ethics mediation. As new media's momentum picks up, the journalistic space between public and professional journalists will need to be shared, and the practices of journalism will have to shift their models for this new form of democratic platform. Through new media and new journalism practices that encourage citizen involvement, journalism is evolving in setting a different standard of what is newsworthy. It is shifting editorial and political agendas to make use of wider content from the public, which could possibly infer the approval of using new journalism models to encourage citizen participation in news making. This research examines how the democratic practice of citizen participation in news content submissions affect news standards, by which the quality of news journalism is evaluated. This paper assesses how news organizations obtain content from citizens, how they make decisions to print and broadcast the content, and asks whether journalism has progressed into a model that involves citizens and professionals in an effective news production process. This study focuses on the implication of acquiring contributions of citizen journalism from the distinctive perspectives of news practices, participatory journalism, and the deliberation of democracy of citizens' press. This paper focuses on how the integration of user-generated content (UGC), in news stories as a vehicle that provides voices for citizens in a democratic movement. The usage of UGC in news institutions has changed traditional journalistic practices in terms of their news value, standard and quality. Essentially, editors of the news media determine which images captured by citizen journalists will be used, and they also decide the messages that they want to send to the public through framing and editing techniques. Previous research on editorial practice has identified various standards about newsworthiness that serve as selection criteria. However, there is a limited amount of research available on how UGC has changed the traditional journalism model. Through qualitative interviews with seven image editors, five news companies, The Canadian Broadcasting Corporation, CTV, Macleans, Rabble and The Toronto Star, this study sheds light on the editor's perceptions about citizen journalist videos and images in news content online. Three Canadian case examples are examined for their visual content analysis: the immigration ex-judge sex bribe case, the Vancouver police tasering of a Polish man, and Victoria police manhandling two young men at a nightclub. Through analysis of the interviews and case studies, this study finds that editors feel that UGC has not altered their traditional news standards. However, upon closer examination of news report cases, it does appear that UGC, which often consists of low quality videos with information entertainment content, has in fact affected the practices of quality journalism. The news media have adopted UGC content styles, which tend toward being more sensational, graphic, raw; these styles can make "hard news", which conveys investigative in-depth information, appear similar to "soft news", such as sensational infotainment. Notwithstanding that professional news organizations use public content in their news stories, they have not provided a platform of partnership to allow citizens to have a democratic voice through their media"--From Abstract.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,009 | 0,012 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,009 |
| Communication savante | 0,013 | 0,009 |
| Science ouverte | 0,001 | 0,005 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
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 source (Gemma direct ou Codex distillé), 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 ».