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Record W2003985723 · doi:10.1080/00438240903430399

Converting to rice: urbanization, Islamization and crops on Pemba Island, Tanzania,<scp>ad</scp>700–1500

2010· article· en· W2003985723 on OpenAlex

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

VenueWorld Archaeology · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Maritime and Colonial Histories
Canadian institutionsSimon Fraser University
FundersLOEWE Zentrum AdRIAWashington University in St. LouisWenner-Gren FoundationNational Science Foundation
KeywordsFoodwaysGeographySwahiliTanzaniaAgricultureSubsistence agricultureLivelihoodUrbanizationBazaarFishingEconomyFisheryArchaeologyEconomic growthEconomicsBiology

Abstract

fetched live from OpenAlex

Abstract Prior to Arab and European imperialism, the farmers of eastern Africa's Swahili coast engaged in a mixed economy, including fishing, animal husbandry and trade in the Indian Ocean's early global economy. This trade network also exposed eastern Africans to new Asian foodways. Botanical data from archaeological sites on northern Pemba Island, Tanzania, show that ancient Pembans first relied heavily on pearl millet, but subsequently became specialized producers of cotton and the Asian crops rice and coconut during the growth of the trading town of Chwaka. This turn towards Asian foodways, particularly rice, was part of a broader alignment with Indian Ocean cultures during a period of urbanization and Islamization along Africa's eastern coast between the eleventh and the fifteenth centuries. Rice specialization was risky due to the constraints of suitable land, rainfall, and labour supply, and it is likely that social and political rewards compelled this agricultural innovation.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.935
Threshold uncertainty score0.862

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.006
GPT teacher head0.249
Teacher spread0.242 · 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