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Record W4391971974 · doi:10.1093/afraf/adae001

Citizen participation during the 2014 protest in Burkina Faso: Aspiring to a ‘good state’

2024· article· en· W4391971974 on OpenAlexfundno aff
Marie-Ève Desrosiers, Nicolas Hubert

Bibliographic record

VenueAfrican Affairs · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican Studies and Ethnography
Canadian institutionsnot available
FundersUniversity of CambridgeUniversity of Ottawa
KeywordsPoliticsState (computer science)Political scienceNeglectPhenomenonPolitical violenceSocial movementPolitical economyGender studiesSociologyLawPsychology

Abstract

fetched live from OpenAlex

Abstract Analyses of the 2014 protest in Burkina Faso have predominantly focused on some of the movement’s major activists, to the neglect of ordinary citizens. Yet, while citizens’ participation in Burkina Faso in 2014 echoed to some extent the agendas of activists, it built on citizens’ own political subjectivities. Drawing on original interviews and Afrobarometer survey data, we show that Burkinabè citizens were motivated to protest by unmet expectations of the ‘good state’, as experienced in their daily existence in the sense of hardship and unequal treatment by the political system. These expectations and aspirations reflected citizens’ deeper political beliefs or political subjectivities, as already expressed in years prior to the 2014 political crisis. Overall, the article shows how looking at protest from the bottom-up can shift our understanding of political mobilization and its motives: citizen protest constitutes its own political phenomenon, in Burkina Faso and beyond, and should not be subsumed by analyses largely derived from speaking to major activists.

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)0.003
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
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.003
Scholarly communication0.0030.002
Open science0.0000.003
Research integrity0.0010.001
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 head0.017
GPT teacher head0.297
Teacher spread0.279 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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