MétaCan
Menu
Back to cohort

New Geographies of Comic Book Production in North America: The New Artisan, Distancing, and the Periodic Social Economy

2003· article· en· W2096688931 on OpenAlexaff
Glen Norcliffe, Olivero Rendace

Bibliographic record

VenueEconomic Geography · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsYork University
Fundersnot available
KeywordsComicsMetropolitan areaDistancingEconomic geographySocial distanceSociologyWork (physics)EconomyProduction (economics)PublishingMedia studiesHistoryGeographyPolitical scienceEconomicsCoronavirus disease 2019 (COVID-19)LawEngineeringArchaeology

Abstract

fetched live from OpenAlex

Abstract: Current interpretations of North American cultural production stress the spatial concentration of these activities in metropolitan centers. There are, however, multiple geographies of cultural production, with other cultural activities deconcentrated and, in some cases, dispersed to distant locations. This situation poses an enigma, since these activities normally form part of a social economy in which networks of personal communication remain important. This paradox is explored using the case of the comic book industry, which has shifted from an in‐house Fordist‐like mode of organization to widespread distancing employing neoartisanal workers who are sometimes located close to the publishing houses, but in other instances are at considerable distances and hence require electronic communication and overnight courier services. Comic book artists often work in isolation but participate from time to time in social activities that are necessary to their creative work. Their work is seen as one of a number of cultural activities that form a periodic social economy with a distinctive time geography.

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)0.000
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.008
Science and technology studies0.0020.004
Scholarly communication0.0030.002
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.010
GPT teacher head0.213
Teacher spread0.203 · 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

Citations99
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueEconomic GeographySame topicCultural Industries and Urban DevelopmentFrench-language works237,207