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Record W2998727043 · doi:10.31124/advance.11472261.v2

Women's Tenure Rights and Land Reform in Angola

2020· preprint· en· W2998727043 on OpenAlexafffund
Allan Cain

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldAgricultural and Biological Sciences
TopicLand Rights and Reforms
Canadian institutionsUniversity of Ottawa
FundersEuropean CommissionInternational Development Research CentreWorld Bank Group
KeywordsLand tenureLivelihoodHuman settlementInheritance (genetic algorithm)LegislationBusinessGovernment (linguistics)Security of tenureLand lawPopulationEconomic growthCustomary landProperty rightsDevelopment economicsPolitical scienceGeographyEconomicsAgricultureLawSociology

Abstract

fetched live from OpenAlex

Current Angolan municipalisation reforms present a unique opportunity to affect local practice on how community and individual land-holder tenure is administered and to protect women's equitable rights to land. Angola is a post-war country, with weak land tenure legislation and limited local government management capacity. Customary traditions are practiced in the various regions a of the country do not respect women's rights of ownership and inheritance. More than 62 percent of the population live in informal settlements with insecure land tenure under the threat of forced evictions. Families living in poor communities affected by the expansion of cities and towns are particularly vulnerable. Of these, families lead by women are the most at risk. Securing rights to land and housing assets are important to livelihoods of women headed households by permitting access to financing that they require to grow their enterprises as well as for incrementally upgrading their housing.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.007
Scholarly communication0.0060.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.017
GPT teacher head0.201
Teacher spread0.185 · 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 designQualitative
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

Citations0
Published2020
Admission routes2
Has abstractyes

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