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Record W1578126709 · doi:10.15353/joci.v4i1.2965

Time, space and the wireless community network

2008· article· en· W1578126709 on OpenAlexaffvenue
Marco Adria

Bibliographic record

VenueThe Journal of Community Informatics · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Communication, and Education
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLaptopWirelessTelecommunicationsWireless networkSpace (punctuation)Computer science

Abstract

fetched live from OpenAlex

Wireless zones are of increasing interest to scholars and practitioners of community informatics because of their promise of universal access to technology. They have been established quickly by municipalities, cooperatives, and private companies, especially in urban centres. A wireless zone may be located either indoors or outdoors, with access to users provided through devices such as laptop computers or personal digital assistants. The spatial organization of wireless zones is inextricably linked to the design of urban spaces and to existing or envisioned transportation routes. Following transportation routes for the design of communication infrastructure has its roots in the 19th-century strategy of threading the telegraph network through the continental railways. The implications of such a strategy for community uses of technology are considered in this article. Drawing on medium theory, I argue that participation in community informatics in an era of virtual identities and mediated communication requires attention to the broad effects of technology, particularly in connection to changing conceptions of time and space. Some implications for community networks are provided.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.008
Scholarly communication0.0060.009
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.050
GPT teacher head0.309
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2008
Admission routes2
Has abstractyes

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