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Record W3193977001 · doi:10.1111/ciso.12406

Urban Precarity and Aspirational Compromise: Feeling Otherwise in a Mozambican Suburb

2021· article· en· W3193977001 on OpenAlexaff
Julie Archambault

Bibliographic record

VenueCity & Society · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicUrban and Rural Development Challenges
Canadian institutionsConcordia University
FundersLeverhulme Trust
KeywordsPrecarityCompromiseTransformative learningSociologyCraftGender studiesNightlifeEthnographyGentrificationAestheticsPolitical scienceEconomic growthGeographySocial scienceAnthropologyArt

Abstract

fetched live from OpenAlex

Abstract The rapidly expanding Mozambican suburb of Inhapossa is very much the product of urban precarity. Indeed, most people only end up there after having exhausted other options. Striking, however, is how residents have, in recent years, discursively and materially constructed the suburb as an idyllic urban place in the making, so much so that Inhapossa has become one of the most coveted neighborhoods in the area. This article proposes an ethnographic reflection on urban precarity that draws on theories “from the South” and extends the notion of suburb to the shifting urban edge in Mozambique. It examines how local land struggles have created new opportunities for people from very different backgrounds, and whose lives became entangled in unexpected life‐enhancing ways, to craft better futures for themselves and their families. Locating the transformative potential of urban precarity in the work of attuning one’s aspirations with one’s circumstances, it shows how the suburb—a space of aspirational compromise—can become a space of aspirational achievement.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.018
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.048
GPT teacher head0.293
Teacher spread0.245 · 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

Citations11
Published2021
Admission routes1
Has abstractyes

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