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Record W3010018393

Politicization in Practice: Learning the Politics of Racialization, Patriarchy, and Settler Colonialism in the Youth Climate Movement

2017· dissertation· en· W3010018393 on OpenAlexaboutno aff
Joe Curnow

Bibliographic record

VenueTSpace · 2017
Typedissertation
Languageen
FieldSocial Sciences
TopicTourism, Volunteerism, and Development
Canadian institutionsnot available
Fundersnot available
KeywordsRacializationPatriarchyGender studiesPoliticsColonialismPolitical scienceMovement (music)SociologyRace (biology)ArtAestheticsLaw
DOInot available

Abstract

fetched live from OpenAlex

As anti-pipeline struggles have become a central focus of the North American environmental movement, the Whiteness, masculinity, and settler-coloniality of the mainstream movement has come under more scrutiny than ever. Though the mainstream environmental movement has long been acknowledged as a White default space, committed to strategies and tactics rooted in settler-colonial logics, and managed by White men at the highest levels, there is a broad conversation emerging right now arguing that the movement needs to unsettle those norms, and urgently. This study looks at one climate campaign as a case study with the potential to reveal both how mainstream environmental spaces become default spaces of Whiteness, masculinity, and settler-coloniality, as well as how these activist groups can become politicized, resisting social relations of dominance and centring reconciliation in their approach to climate justice. Using sociocultural theory as the lens for theorizing learning within the climate movement, this dissertation brings learning within social movements into focus, examining cognition, participation, ways of knowing and being, and identity development across a two-year activist campaign. This dissertation examines Fossil Free UofT, the University of Toronto campaign for fossil fuel divestment. I ask how participants learned to understand and disrupt social relations of racialization, settler colonialism, and patriarchy. I examine what participants in the campaign learned and how they mobilized their learning collectively to reproduce and resist racialized, gendered, and colonial power relations. I also question how sociocultural theories of learning enable theorizations of politicization, as well as how they can be strengthened through sustained attention to the ways that social relations shape opportunities to learn in movements. This dissertation contributes to an emergent field in the learning sciences, where social movements and community organizations are increasingly analyzed for their ability to foment unique learning opportunities. I theorize politicization within this context, providing a framework for sociocultural learning theorists to bring together disparate conversations about learning, civic engagement, sociopolitical development, and critical social analysis.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.070
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.023
GPT teacher head0.378
Teacher spread0.355 · 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 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
Published2017
Admission routes1
Has abstractyes

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