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Record W6995970787

Race, power and social action in neighbourhood community organizing: a case study

2010· dissertation· en· W6995970787 on OpenAlexaboutno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2010
Typedissertation
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsnot available
Fundersnot available
KeywordsEthnic groupRace (biology)Neighbourhood (mathematics)Power (physics)Community organizationCommunity organizingSocial constructionism
DOInot available

Abstract

fetched live from OpenAlex

This thesis asks the following question: "how does race and ethnicity emerge in the daily practice of community organizers who work in low-income, multi-racial, multi-ethnic neighbourhoods?" Given that the concepts of race and ethnicity are understood to be social constructs, community organizing practice is analysed in this thesis in terms of its' constitutive role. By examining community organizing practice in one neighbourhood in Québec, Canada, I argue that issues of race and ethnicity are largely constructed in community organizing practice as distinct from relations of power. I demonstrate this construction of race and ethnicity using data gathered from 16 community organizers through interviews, textual analysis and observations. I analyse the data from three angles: first, actions regarding issues of race and ethnicity that are normalized (i.e. "possible"); second, actions regarding issues of race and ethnicity that are constrained (i.e. "not possible"); and, lastly, actions that are resistant to normalized and/or constrained practices, and that link race and ethnicity to power relations. In this way, I delineate Foucault's "field of action" (1982, p. 221) regarding race and ethnicity in neighbourhood community organizing and demonstrate how the structure of power in community organizing functions to render the connection between race and power largely invisible.

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)0.005
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesResearch integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0140.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0020.019
Insufficient payload (model declined to judge)0.0010.000

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 head0.077
GPT teacher head0.399
Teacher spread0.322 · 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; both teacher heads agree on what is shown here.

Study designOther design
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
Published2010
Admission routes1
Has abstractyes

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