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Record W2029079347 · doi:10.4000/civilisations.405

Remote Control Research in Central Africa

2006· article· en· W2029079347 on OpenAlexaff
Théodore Trefon, Serge Cogels

Bibliographic record

VenueCivilisations · 2006
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Rural Development Research
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsPresentation (obstetrics)Control (management)Field (mathematics)Process (computing)Identification (biology)Field researchSelection (genetic algorithm)Protocol (science)Process managementPolitical scienceSociologyManagement scienceComputer scienceBusinessEngineeringManagementSocial scienceEconomics

Abstract

fetched live from OpenAlex

This article explains how a project being implemented in peri-urban central Africa is coordinated from an office in Brussels. After an overview that addresses the conceptual challenges of defining ‘peri-urban’ and the question of why these social spaces are important from a development perspective, the article outlines ‘remote control research’ step-by-step: (i) conceptualisation, (ii) identification and recruitment of local experts, (iii) selection of research sites, (iv) the process of formulating a locally appropriate and detailed research protocol, (v) implementation and (vi) analysis of findings and presentation of results. The conclusion argues that research in central Africa will increasingly be influenced by donor priorities and will consequently need to respect the guidelines dictated by project cycle management strategies currently in vogue. The steps in the project cycle reflect the nature of the relationships between donors, researchers in the field and the intermediary project managers that link the two extremes. Accommodating the worldviews, expectations and constraints of these actors is something that, although not always easy, is possible when the right blend of conditions is respected.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.705
Threshold uncertainty score0.693

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.277
Teacher spread0.222 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2006
Admission routes1
Has abstractyes

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