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Record W4384697487 · doi:10.22215/etd/2023-15558

Now You See Us: The Politics of Visibility in Mumbai’s “Slum” Activism

2023· dissertation· en· W4384697487 on OpenAlexafffund
Anelynda Mielke

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicWater Governance and Infrastructure
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of CanadaScheme for Promotion of Academic and Research Collaboration
KeywordsPoliticsPerformative utteranceSociologyPolitical sciencePremisePublic relationsSocial movementMedia studiesGender studiesLawAesthetics

Abstract

fetched live from OpenAlex

My research contributes to the fields of politics of visibility and visual culture, as well as material politics or the 'politics of things' and infrastructure.I build on the suggestion that visibility is not to be simply conflated with either social recognition or control and discipline.I examine the various registers of visibility, and how they intersect with the politics of physical objects and infrastructures in the lived experiences of informal settlement activists in Mumbai.I use the language of assemblages to describe the web of human and nonhuman actors involved in activist organizing.My three core arguments emphasize the centrality of a politics of visibility in the activism context in Mumbai.Activists' main role is to direct visibility; this is the common thread connecting activists' activities.Activism is not a calculated attempt to gain resource access.It is a chance to be seen differently.Activist belonging is attached to performative demands which open activist leadership to the criticism that the performance in fact might hinder the stated intentions of the movement; how could new spaces open for accessing scarce resources if notion of the 'good activist' were set aside?This examination centres on ethnographic fieldwork conducted over approximately 18 months in Mumbai, including interviews and conversations with government, nongovernmental, and private sector actors, as well as many activists living inside and outside of informal settlements.I worked with the activist organization Slum Community Action Foundation (SCAF) headed by Vithal Chavan and the much larger, well-established social movement Ghar Bachao Ghar Banao Andolan (GBGBA) under the leadership of Medha Patkar.My perspective comes from embedding myself within activist movements by attending meetings, sharing meals, visiting their homes, co-authoring articles, and traveling with an activist leader and a group of activists to central Maharashtra.This work hopes to open new spaces of inquiry to advance understandings of citizenship and social movements, and to support further scholarship focused on ethnographic methods to explore materiality, visibility, and social movements as an assemblage of human and nonhuman relationships.completing this dissertation.He understood my desire to write something accessible, yet well-informed.His wealth of knowledge spanning multiple bodies of research enabled my cross-disciplinary approach.Thanks also to my committee, Dr. Daiva Stasiulis and Dr. Gopika Solanki, who provided input throughout.My perspective on Visual Culture and the politics of visibility was also greatly enriched through the contributions of Dr. Christiane Wilke, a member of my committee for my first Comprehensive Examination.I am grateful to the Administration and leadership of Carleton's Sociology and Anthropology Department, including especially Dr. Alexis Shotwell for guidance, encouragement, and support in this process.I also appreciate the camaraderie offered by my fellow PhD students in my cohort, particularly during the early stages of the

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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.026
Scholarly communication0.0110.005
Open science0.0010.010
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.015
GPT teacher head0.313
Teacher spread0.298 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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