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Communicative Ecologies: Editorial Preface

2007· article· en· W1587329064 sur OpenAlexfundaboutno aff
Greg Hearn, Marcus Foth

Notice bibliographique

RevueQUT ePrints (Queensland University of Technology) · 2007
Typearticle
Langueen
DomaineSocial Sciences
ThématiqueMedia, Communication, and Education
Établissements canadiensnon disponible
Organismes subventionnairesCape Peninsula University of TechnologyUniversity of TorontoAalborg UniversitetCalifornia State University, FullertonQueensland University of TechnologyUniversity of WestminsterGrand Valley State UniversityMonash UniversityVictoria University of WellingtonVictoria UniversityMassachusetts Institute of Technology
Mots-clésMedia ecologyEcologySociologyFraming (construction)PopulationContext (archaeology)Media studiesGeographyBiology
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The term 'ecology' has a lot to offer communication research. This biological analogy opens up research into time and space dynamics, population growth and lifecycles, networks, clusters, niches, and even power relationships between pray and predators. The research perspective may be at either holistic (macro) or individual (micro) levels of analysis. In McLuhan and Postman's tradition of media ecology the concept takes a media-centric view referring to the way in which media structure our lives and how they influence society. The focus of this special issue, the concept of 'communicative ecology', is different insofar as we put an increased emphasis on the meaning that can be derived from the socio-cultural framing and analysis of the local context which communication occurs in. We define a communicative ecology as a milieu of agents who are connected in various ways by various exchanges of mediated and unmediated forms of communication (Tacchi et al., 2003 ). From a communicative ecology perspective each instance of media use is considered at both individual and community level as part of a complex media environment that is socially and culturally framed. We do not limit the scope of analysis to traditional print, broadcast and telecommunication media but include social networking applications for peer to peer modes of communication, transport infrastructure that enable face to face interaction, as well as public and private places where people meet, chat, gossip. We conceive of a communicative ecology as having three layers (Foth & Hearn, 2007). A technological layer which consists of the devices and connecting media that enable communication and interaction. A social layer which consists of people and social modes of organising those people - which might include, for example, everything from friendship groups to more formal community organizations, as well as companies or legal entities. And finally, a discursive layer which is the content of communication - that is, the ideas or themes that constitute the known social universe that the ecology operates in. Using an ecological metaphor opens up a number of interesting possibilities for analyzing place-based communication (e.g., in neighbourhoods, apartment buildings, or - on a larger scale - suburbs and cities). It can help us to better understand the ways social activities are organized, the ways people define and experience their environments, and the implications for social order and organization. For example, in analyzing an apartment complex, an ecological metaphor might suggest first examining the features of the population in the apartment and mapping the patterns of engagement within that population. In addition we could ask how people relate to different places within the apartment, and how this interaction is mediated by the use of technology. Do different groups form around a coffee shop? Do email or cell phone connections define other ecologies? Then we might also be able to study transactions between different ecologies. The ecological metaphor focuses on whole of system interactions. It also enables us to define boundaries of any given ecology, and to examine how the coherence of that boundary and the stability of each ecology is maintained. What topics of conversation define insiders and outsiders in the ecology? Finally, it also opens up the question of the social sustainability of a communicative ecology. Similar sorts of questions have been asked by the contributors to this special issue who research human communication phenomena in various place-based contexts. The first article "Comparing the Communication Ecologies of Geo-ethnic Communities: How People Stay on Top of Their Community" by Wilkin et al. highlight the benefits to be gained from a communicative ecology approach by presenting a communication map to help communicate with ethnically diverse populations. Shepherd et al. follow with their contribution "The Material Ecologies of Domestic ICTs" which examines the socio-cultural context of the media and communication environments we create in our homes. The next article "Primary Attention Groups: A Conceptual Aproach to the Communicative Ecology of Individual Community in the Information Age" by Allison applies the layer model described above to analyse individual social groupings. Peeples and Mitchell also found the layer model useful in exploring the 1999 WTO protests in "No Mobs - No Confusions - No Tumult: Organizing Civil Disobedience". Powell's article "An Ecology of Public Internet Access: Exploring contextual internet access in an urban community" concludes this special issue by offering a detailed account of the role public internet access plays in the communicative ecology of inner-city residents. We thank our colleagues for their help and assistance in providing an extraordinary high quality of peer review for this special issue of EJC: Corey Anton, Grand Valley State University; Elija Cassidy, Queensland University of Technology; Christy Collis, Queensland University of Technology; Victor Gonzalez, University of Manchester; Phil Graham, Queensland University of Technology; Joshua Green, Massachusetts Institute of Technology; Deborah Jones, Victoria University of Wellington; Jesper Kjeldskov, Aalborg University; Mark Latonero, California State University, Fullerton; Graham Longford, University of Toronto; Harvey May, Queensland University of Technology; Lucy Montgomery, University of Westminster; Tanya Notley, Queensland University of Technology; Christine Satchell, University of Melbourne; Larry Stillman, Monash University; Jo Tacchi, Queensland University of Technology; Wallace Taylor, Cape Peninsula University of Technology; Tommaso Venturini, University of Milano - Bicocca. Our work is supported under the Australian Research Council's Discovery funding scheme (project number DP0663854) and Dr Marcus Foth is the recipient of an ARC Australian Postdoctoral Fellowship. Foth, M., & Hearn, G. (2007, forthcoming). Networked individualism of urban residents: Discovering the communicative ecology in inner-city apartment complexes. Information, Communication & Society, 10(5). Tacchi, J., Slater, D., & Hearn, G. (2003). Ethnographic action research handbook. New Delhi, India: UNESCO.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,699
Score d'incertitude au seuil0,489

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,018
Tête enseignante GPT0,291
Écart entre enseignants0,273 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations54
Publié2007
Routes d'admission2
Résumé présentoui

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