MétaCan
Menu
Retour à la cohorte
Enregistrement W29378538 · doi:10.3233/iwa-2003-00028

Charting and Bridging Digital Divides

2003· article· en· W29378538 sur OpenAlexaff
Wenhong Chen, Barry Wellman

Notice bibliographique

RevueI-WAYS Digest of Electronic Commerce Policy and Regulation · 2003
Typearticle
Langueen
DomaineEngineering
ThématiqueICT Impact and Policies
Établissements canadiensUniversity of Toronto
Organismes subventionnairesnon disponible
Mots-clésDigital divideThe InternetGlobeBridging (networking)Internet accessInternet privacyPolitical scienceComputer scienceWorld Wide WebComputer securityPsychology

Résumé

récupéré en direct d'OpenAlex

Many assume that the digital divide – the large numbers of people who are not connected to the Internet – is small, shrinking, and rapidly becoming irrelevant. It is not. The term “digital divide” refers to inequalities in Internet access and use, ranging from the global level, to nation states, to communities, and to individuals. The divide is here for some time to come. It is large, multifaceted, and, in some ways, it is not shrinking. Moreover, the divide is socially patterned, so that there are systematic and meaningful variations in the kinds of people who are on and off the Internet. These patterns vary between nations and over time, so last year’s divide often does not necessarily resemble this year’s, and Country A’s divide does not necessarily resemble Country B’s. Indeed, it is more accurate to use the plural – digital divides – because the nature of the digital divide varies within and between countries, both developed and developing. There is no one digital divide; there are many divides. To be sure, the Internet has grown rapidly and hugely in the last decade. Educated estimates show that use of the Internet has diffused to the point that the number of Internet users around the globe has surged from 900,000 in 1993, 25 million in 1995, 83 million in 1999, 513 million in 2001, to more than 600 million by the end of 2002. More recently, other new media, such as Web-enabled mobile phones, have fostered computermediated technology. Yet, widespread diffusion does not equal ubiquity, even within developed countries. The first digital divide appeared at the very start of the Internet. Early users were disproportionately affluent, male, white, better educated, and from developed countries, especially the United States. Rather than shrinking with expanding Internet use, the global digital divide between developed countries and developing nations continues to be huge. Denizens of economically developed countries sometimes forget what a small percentage of the world’s population is online. After all, the majority of their country-mates are on the Internet, as are the economically advanced segments of developing countries. Yet, only 10 percent of the world’s population was on the Internet in 2002, and 88 percent of these Internet users resided in industrialized countries. Within countries, the uneven diffusion of the Internet appears along familiar lines of social inequality such as socioeconomic status, gender, age, geographic location, and ethnicity. Moreover, having access to computers and the Internet and possessing the ability to use them effectively are two different issues. However, marketers, media, and governments often report only the number of people who have access to the Internet. The question is not whether people have ever glanced at a monitor or put their hands on a keyboard, but the extent to which they regularly use a computer and the Internet for meaningful purposes. At present, the digital divide has multiple aspects. As noted above, it is really digital divides. First, the digital divide is not a binary yes/no question of whether the basic physical access to the Internet is available. Access does not equal use. Rather, the digital divide is a continuum ranging from physical access, financial access, cognitive access, and content access to political access. Second, the term “digital divide” has both technological and social resonances. There are at least five

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,749
Score d'incertitude au seuil0,490

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
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 Opus0,011
Tête enseignante GPT0,229
Écart entre enseignants0,218 · 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'étudeThéorique ou conceptuel
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

Citations18
Publié2003
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueI-WAYS Digest of Electronic Commerce Policy and RegulationMême sujetICT Impact and PoliciesTravaux en français237 207