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Record W2891465749 · doi:10.1386/public.29.57.228_7

ACTIVATING HISTORY: The Living Counter-Archive of Urban Vernacular Paths

2018· article· en· W2891465749 on OpenAlexaff
Benjamin Peter Fodden Prus

Bibliographic record

VenuePublic · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSoutheast Asian Sociopolitical Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsVernacularNeighbourhood (mathematics)TRACE (psycholinguistics)Key (lock)Industrial citySociologyHistoryComputer scienceArtRegional scienceLiteratureComputer security

Abstract

fetched live from OpenAlex

Abstract The project began with mapping a series of informal paths and shortcuts (17 in total) created by Hamiltonians. These paths have been carved into the ground by years of repeated trespassing to, from, and across railway tracks. The inscriptions of countless footfalls, the paths form an archive of local residents’ movements through their neighbourhood. The railway is representative of formal urban planning and Hamilton’s industrial past, while the informal paths trace anonymous, everyday ways that citizens break the “rules” of the formally planned city. To highlight the importance of these paths in the lives of the local community, I erected fake notices of the City of Hamilton’s intent to formally name these informal walkways. The formal names of city streets and paths are a way for a city to officially archive particular histories, while overlooking others. The forged notices stimulated discussion in the local community around key issues: which histories get kept and whose are discarded, who has the right to name what is created by local residents, and what is the “right” way to live and move within the city?

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 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)0.001
metaresearch head score (Gemma)0.003
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: none
Teacher disagreement score0.830
Threshold uncertainty score0.629

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
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 head0.044
GPT teacher head0.286
Teacher spread0.242 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2018
Admission routes1
Has abstractyes

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