MétaCan
Menu
Back to cohort
Record W4390022603 · doi:10.1111/gec3.12732

Problematizing urban microtoponyms

2023· article· en· W4390022603 on OpenAlexaff
Sergei Basik

Bibliographic record

VenueGeography Compass · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsConestoga College
Fundersnot available
KeywordsToponymyVernacularPerspective (graphical)PoliticsSociologyField (mathematics)Subject (documents)Everyday lifeGeographyEpistemologyHistoryLinguisticsArchaeologyPolitical scienceComputer scienceLawPhilosophyArtVisual arts

Abstract

fetched live from OpenAlex

Abstract A spatial perspective on microtoponyms, informal non‐standardized names of small objects and places known to the locals, is an often‐neglected segment of urban political toponymic theory and practice. Though critically‐oriented thinkers have acknowledged the role of vernacular place names in the spatial organization of symbolic cultural landscapes, place‐making processes, and the everyday life of people and their communities, conceptual spatial‐political theorizations on this subject have been relatively rare. Driven upon the critical toponymic theory, this paper aims to delineate a conceptual framework for studying urban microtoponyms as spatial phenomena by integrating the toponymic plurality notion. Based on examples primarily from non‐Western geographical contexts, this paper offers a fresh perspective on urban place naming practices and related spatial processes providing some analytical pathways for critical scholars in urban toponymy and guiding potential empirical investigations in this field.

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)0.007
metaresearch head score (Gemma)0.016
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 score0.007
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.005
Science and technology studies0.0060.018
Scholarly communication0.0070.015
Open science0.0020.009
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.031
GPT teacher head0.316
Teacher spread0.285 · 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

Citations6
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueGeography CompassSame topicGeographies of human-animal interactionsFrench-language works237,207