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Record W4415097338 · doi:10.1080/00220388.2025.2569390

Truth in Translation: An Ethnographic Exploration of the Everyday Practices of Monitoring in a Senegalese Sustainable Development NGO

2025· article· en· W4415097338 on OpenAlex
Mathilde Gouin-Bonenfant

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Journal of Development Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Development and Aid
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsEthnographySustainable developmentGovernment (linguistics)Work (physics)SustainabilityContext (archaeology)

Abstract

fetched live from OpenAlex

This article, based on 12 months of ethnographic fieldwork in the Saloum Delta, in Senegal, investigates the relationship between Results-Based Management (RBM) and the difficulties, faced by many NGOs, to understand the needs and desires of the communities with whom they work. The article follows the day-to-day monitoring practices of one sustainable development NGO, and highlights the influence of RBM on the possibility of ‘knowing the truth.’ The article shows how the culture, language, and tools of RBM impact the ecosystem of relationships surrounding the NGO, creating a culture rooted in evidence production, justification, and suspicion. By taking an interactional and linguistic approach, the article also shows the limits and possibilities of producing coherence and success within monitoring activities.

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.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.280
Threshold uncertainty score0.260

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.134
GPT teacher head0.411
Teacher spread0.277 · 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