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Record W2052025399 · doi:10.1177/1077800408322708

Of Walking Shoes, Boats, Golf Carts, Bicycles, and a Slow Technoculture

2008· article· en· W2052025399 on OpenAlexaff
Phillip Vannini, April Vannini

Bibliographic record

VenueQualitative Inquiry · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicMedia, Communication, and Education
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsEthnographyEmbodied cognitionArgument (complex analysis)ReflexivitySociologyMedia ecologyAestheticsSymbolic interactionismParticipant observationMovement (music)Media studiesArtEpistemologyAnthropologySocial science

Abstract

fetched live from OpenAlex

Drawing on participant observation conducted on Protection Island, British Columbia, this article examines the significance of technologies of movement and, in particular, embodied media. It advances the argument that embodied media (i.e., technologies of transportation) differ significantly from disembodied media (traditional information media and new media). Utilizing media ecology and symbolic interactionist theory, this visual, sensuous, reflexive, poetic, McLuhanesque ethnography shows how the uniqueness of technoculture on Protection Island is due to the unique local patterns of interaction between techniques and technics of movement. Such patterns are conceptualized as "heavy" and "slow," and their consequences for social relationships, and in particular the structure of space, are described and interpreted. Also discussed is the role of technography or ethnography of technology.

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)0.001
metaresearch head score (Gemma)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.070
Threshold uncertainty score0.139

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.011
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.162
GPT teacher head0.439
Teacher spread0.277 · 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

Citations15
Published2008
Admission routes1
Has abstractyes

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