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Record W7042471758

The political economy of titling in Jamaican urban informal settlements

2024· other· en· W7042471758 on OpenAlexaff

Bibliographic record

VenueLund University Publications Student Papers (Lund University) · 2024
Typeother
Languageen
FieldArts and Humanities
TopicClassical Studies and Legal History
Canadian institutionsInternational Development Research Centre
Fundersnot available
KeywordsLand titlingPovertyInformal settlementsGovernment (linguistics)State (computer science)Property rightsInformal sectorRelevance (law)Institution
DOInot available

Abstract

fetched live from OpenAlex

This qualitative study investigates how formalization of private property rights through titling affects poverty dynamics in urban informal settlements in Jamaica, a small “developing” state. It relies on a case study to explore the impact of titling on tenure security, housing investment, access to credit, and gender poverty and the factors that support or constrain titling initiatives. Given the relevance of the state and the efficacy of its institutions, this research uses a political economy approach to explain the institutional structures and power relationships that shape the environment in which titling programs are embedded. Data were collected through 12 semi-structured interviews, a questionnaire survey, and secondary sources, including Government of Jamaica publications and reports from donor agencies, which were analyzed using thematic analysis. Results suggest that titles enhanced resident’s sense of ownership of their property, facilitated credit access only for better educated and higher income earners, and that the state’s failure to consider women’s reproductive needs is a missed opportunity to help improve livelihoods. Findings also suggest, counter to neoliberal economic theories, that greater state involvement, particularly in the provision of basic services and improved institutional capacity, is necessary for titles to serve as a meaningful poverty reduction strategy.

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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.769
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.200
Teacher spread0.188 · 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 teacher head, not a consensus.

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

Citations0
Published2024
Admission routes1
Has abstractyes

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