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Record W3126353788 · doi:10.1111/blar.13148

Organising Everyday Resistance: An Ethnographic Study of Rickshaw Drivers in Bogotá

2021· article· en· W3126353788 on OpenAlexfundno aff
Ana Maria Vargas Falla

Bibliographic record

VenueBulletin of Latin American Research · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicCrime, Illicit Activities, and Governance
Canadian institutionsnot available
FundersConcordia University
KeywordsResistance (ecology)OppressionEthnographyArgument (complex analysis)SociologyEveryday lifeCriminologyGender studiesLawPolitical sciencePoliticsAnthropologyMedicine

Abstract

fetched live from OpenAlex

Workers in the informal transport sector are often exposed to multiple forms of workplace violence, for instance by the police and their colleagues. Through a collection of rich ethnographic stories and using the concept of popular resistance, this article investigates how and under what conditions rickshaw drivers in Bogotá resist violence in their workplace. The results reveal that rickshaw associations have been essential in articulating acts of everyday resistance to the legal ban on this activity, such regulating routes, fees and stops. However, associations have created new forms of oppression, being labelled as mafia‐like organisations, showing that resistance can also translate into new forms of domination. Contrary to the argument that everyday resistance is uncoordinated, this article shows that acts of everyday resistance can be organised by actors that switch between different individual and collective strategies. Thus, organisations can provide a framework to resist the law on an everyday basis.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.040
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0080.007
Scholarly communication0.0040.004
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.097
GPT teacher head0.414
Teacher spread0.317 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueBulletin of Latin American ResearchSame topicCrime, Illicit Activities, and GovernanceFrench-language works237,207