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Mobile Media as New Forms of Spatialization

2015· article· en· W2157112353 on OpenAlexafffund
Luciano Frizzera

Bibliographic record

VenueInterdisciplinary Science Reviews · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsSimon Fraser University
FundersUniversity of Alberta
KeywordsSpatializationSpace (punctuation)sortComputer scienceHegemonyExpression (computer science)Social mediaPower (physics)Human–computer interactionInterface (matter)MultimediaInternet privacySociologyWorld Wide WebPolitical sciencePolitics

Abstract

fetched live from OpenAlex

The physical space has historically served as an important support for human expression. However, the production of location-based information has been consciously used as means of social control by the hegemonic power, which decides what can be publicly displayed, and what should be hidden. With the development of mobile media, space has gained new dimensions, resulting in a sort of hybrid space where digital information overlays the physical space revealing what was previous unknown about a place. As mobile devices become increasingly present in our society, they should be understood as a social interface to our experience of space, serving not only as means to consume information, but also tools for communication. This paper discuss the current mobile media practices, such as mapping, urban electronic annotations, location-based mobile games, and smart mobs, which creates opportunities for new forms of human expression, reappropriations of space, and contestation of hegemonic power.

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)0.003
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.004
Science and technology studies0.0030.028
Scholarly communication0.0150.016
Open science0.0010.008
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.075
GPT teacher head0.410
Teacher spread0.335 · 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 designTheoretical or conceptual
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

Citations14
Published2015
Admission routes2
Has abstractyes

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