Joanny Bélair. Tanzania’s Land Rush: Impacts of the Farmland Investment Game. New York: Bloomsbury, 2023. xxiii + 163 pp. Illustrations. Notes. References. Index. $58.50. Paper. ISBN: 9781350273931.
Bibliographic record
Abstract
Tanzania's Land Rush explores how political actors, investors, and farmers jostle over land, the power to determine access to it, and the benefits that flow from this power.Following a brief introduction to the book's theoretical framework and the topic of large-scale land investments in sub-Saharan Africa, Chapter Two sets out to debunk several "unquestioned and unproven assumptions" (20) about this phenomenon.While the existence of a voluminous literature, parts of which Bélair relies on to issue her correctives, makes it debateable just how unquestioned these assumptions are, she notes that land in sub-Saharan Africa is, contrary to perceptions, typically not in fact un-or underutilized; that investment in it, therefore, typically cannot avoid dispossession; and that assumed benefits, such as employment creation or productivity improvements, often fail to materialize.This is perhaps not very surprising when familiar wheeling and dealing around land acquisitions-besides speculation, Bélair cites as possible side-benefits access to bank loans, produce trading, and hunting in the vicinity of a national park-takes the focus and onus off agricultural production.Chapter Three provides a somewhat unfocused political history of Tanzania and a barebones sketch of the country's complex land tenure regime, a firmer grasp of which may have helped avoid problems in Chapter Four.There, Bélair for instance interprets a still-not-enacted 2018 reform proposal of Tanzania's National Land Policy as an attempt to reshape institutions with the goal of "strengthening the discretionary power of the President" (55).She cites as evidence provisions giving the president the power to declare eminent domain and approve village assemblies' decisions to transfer village-controlled lands into a category that allows investors to gain access.But these provisions simply reassert existing presidential powers under the 1999 Village Land Act.Such longstanding statist aspects of the land regime, in addition to enduring communal, village control over about two-thirds of Tanzania's lands and the recognition of customary rights, also sit uncomfortably with Bélair's assertion that land policy has, since the 1980s, "eagerly embraced neoliberal ideas and discourse" (47).Likewise, a section on the arbitrary powers exercised by local officials in the demarcation of village lands operates under the assumption that these are precisely knowable areas.When officials then "mis-record" them, this must, ipso facto, be purposive, that is, corrupt.A more searching analysis may have taken its starting point from an acknowledgement of a central conundrum of Tanzania's
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".