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Record W4313010333 · doi:10.1596/38262

Towards a More Inclusive Zanzibar Economy

2022· book· en· W4313010333 on OpenAlexfundno aff

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicGlobal Maritime and Colonial Histories
Canadian institutionsnot available
FundersOntario Council on Graduate Studies, Council of Ontario Universities
KeywordsTanzaniaGeographyEnvironmental planning

Abstract

fetched live from OpenAlex

This report assesses recent progress in poverty reduction in Zanzibar.It is based on Zanzibar's last three household budget surveys and considers the period between 2009 and 2019, with a focus on the last four years of this decade: 2015-2019.Poverty -based on household consumption -fell by 9 percentage points over the decade before the COVID-19 pandemic: it dropped from 34.9 to 25.7 percent.However, the pace of poverty reduction was slow relative to population growth and as such, the number of poor dropped by only 27,000.The drop was fastest in urban areas and because poverty levels were already lower than in rural areas, the gap between rural and urban poverty widened, driven by differences between the islands of Unguja and Pemba.Simulations suggest that the COVID-19 pandemic increased urban poverty increased by 1.8 percentage points in 2020-21 while rural poverty dropped by 0.8 percentage points.Substantial progress was also made across a range of non-monetary poverty indicators, notably in improved access to basic services including electricity and education.During the period 2009-2019, access to the electricity network increased from 38 to 57 percent, while education indicators also improved considerably.For example, between 2015 and 2019, lower secondary gross enrolment went up from 68 to 90 percent.Despite progress, gaps remain especially among the poor living in rural areas, notably in Pemba.Results from a multi-dimensional poverty index (MPI) calculated based on 3 dimensions and 13 indicators using the HBS 2019-20 indicate that 36.6 percent of Zanzibaris were multi-dimensionally poor, that is, they were deprived in at least a third of the MPI indicators used.The relationship between economic growth and poverty reduction was weak as during 2009-19 growth did not sufficiently translate into improved well-being of the poorest.Although during the period 2014 to 2020-21 Zanzibar witnessed a large shift of people out of low-productivity agriculture into services, particularly of women (a 10-percentage point shift according to labor force survey data), 'decomposition analysis' shows that population shifts to other sectors of work barely contributed to poverty reduction.Many likely adopted low-productivity work in the services sector.In fact, the creation of quality jobs was limited, and informality increased during this period.To accelerate poverty reduction in Zanzibar, a combination of policies are required to (i) make tourism, the main growth engine of the economy, more inclusive, for example through the diversification of tourism products; (ii) improve labor market outcomes for women and youth through better skills training and internship programs; (iii) improve the distribution of public spending in education and health to make it more pro-poor; and (iv) improve the business operating and regulatory environment of SMEs and better connect farm smallholders to high-value markets to enhance value addition, job creation and poverty reduction.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0050.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0140.006

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.

Opus teacher head0.010
GPT teacher head0.275
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2022
Admission routes1
Has abstractyes

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