MétaCan
Menu
Back to cohort
Record W2502768764 · doi:10.5210/fm.v21i8.6724

Ordering space: Alternative views of ICT and geography

2016· article· en· W2502768764 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFirst Monday · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGeographic Information Systems Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsICTSInformation and Communications TechnologySpace (punctuation)Locale (computer software)EpistemologyContrast (vision)SociologyComputer scienceData scienceEconomic geographyGeographyWorld Wide WebArtificial intelligencePhilosophy

Abstract

fetched live from OpenAlex

We analyze two ways of thinking about ICTs in the production of space. One is what we call the “mimetic” view. This view focuses on ICTs’ ability to bring representations from one locale into another. Debates about ICTs and geography have historically been driven by this “mimetic” view and continue to be constrained by it. In contrast, we discuss what we call the “algorithmic” view of ICTs, which focuses on computational re-ordering of representations and subsequent reordering of real-world entities. Recently, scholars of ICTs, communication, and geography have increasingly drawn on examples that fall under the “algorithmic” view, yet the distinction between the two views has not been clearly articulated. This paper clarifies this distinction.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.933
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.278
Teacher spread0.253 · 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