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Record W4220842546 · doi:10.1017/s0963926822000013

‘Look out! Get back!’ Horse-drawn traffic and its challenges in Belgian cities in the early modern period

2022· article· en· W4220842546 on OpenAlexaff
William Riguelle

Bibliographic record

VenueUrban History · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPeriod (music)PhysiognomyFace (sociological concept)HistoryGeographyEconomyPolitical scienceSociologyArtSocial scienceEconomics

Abstract

fetched live from OpenAlex

Abstract The horses transporting men and merchandise were key actors in urban development at the very time they placed the city's ability to organize and adapt in doubt. Cities of the southernmost Netherlands and the Principality of Liège were forced to cope with the constant challenge represented by traffic in poorly designed arteries, with a morphology inherited from the medieval period and completely ill-suited to the movement of carriages and wagons. The problem posed by traffic in Belgian cities reached a critical threshold in the seventeenth century, a period in which we observe an increase in the number of horses and harnessed teams. The complications caused by this growing surge culminated in the next century and were marked by the formation of a police force obliged to face the challenge traffic represented. Consequently, numerous urban decisions were taken, transforming both the street's ‘lifestyle’ and physiognomy.

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)0.001
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.771

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0040.005
Scholarly communication0.0040.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.055
GPT teacher head0.193
Teacher spread0.138 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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