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Record W2885992806 · doi:10.1017/s0022278x18000289

Land investments in Tanzania: assessing the role of state brokers

2018· article· en· W2885992806 on OpenAlex
Joanny Bélair

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Modern African Studies · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture, Land Use, Rural Development
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTanzaniaPossession (linguistics)IntermediaryLocal governmentState (computer science)Context (archaeology)BusinessLand tenureCentral governmentEconomicsEconomic systemFinanceGeographyPolitical sciencePublic administrationSocioeconomics

Abstract

fetched live from OpenAlex

Abstract Focusing on one of the most targeted areas for land investments in Tanzania (Rufiji district), this article compares the involvement of two Tanzanian state agencies in land acquisition, in the context of the central government's new strategy on productive investors. Given the fragmented and contentious authority of many African states, I investigate the impact of state intermediaries on the relationships between investors and local populations and consider bureaucrats as a group of actors to analyse flows of power within the state. I make two main points. First, the central state's weak infrastructural power and resulting lack of local knowledge, and, conversely, local bureaucrats’ possession of these valuable resources, reverses the flow of power from local to central. Second, a central monitoring process might have a negative effect. Instead of protecting vulnerable populations, it fosters institutional innovations that protect local bureaucrats’ opportunities for accumulation with investors, to the detriment of local populations.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.350
Threshold uncertainty score0.155

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.029
GPT teacher head0.261
Teacher spread0.232 · 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