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Understanding the Weak Performance of Technology in Urban Management

2016· book-chapter· en· W4248424834 on OpenAlexaff
Claire Simonneau

Bibliographic record

VenueInternational Business · 2016
Typebook-chapter
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsAppropriationEthnographySection (typography)ObsolescencePoliticsContext (archaeology)SociologyUrban planningKnowledge managementManagement scienceRegional sciencePolitical sciencePublic relationsEngineeringEpistemologyGeographyComputer scienceCivil engineeringBusinessMarketing

Abstract

fetched live from OpenAlex

The article questions the appropriation of existing urban planning and management tools in Sub-Saharan Africa, through a multiple case study: the implementation of a land information system (or simplified cadastre) in three cities in Benin. An ethnographic exploration of the use of the tool is conducted. The first section presents the historical context of the design of land information systems, framed by the urban management paradigm, and unwarranted confidence in new technologies. The second section presents the theoretical framework and the methodology of the research, inspired by public policy analysis and development anthropology. The third section describes findings of the multiple case studies. A vicious circle is highlighted, made up of: lack of political support, obsolescence, and decline of cost-effectiveness. The fourth section discusses the results of the ethnographic inquiry. These are, essentially, the interpretation of the paradoxes, blockages, and conflicts in the implementation of the tool in light of social, political and economic dynamics that take place at the local level, although unexpected by the creators of the tool.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.853
Threshold uncertainty score0.500

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.066
GPT teacher head0.266
Teacher spread0.201 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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
Published2016
Admission routes1
Has abstractyes

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