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Record W7052129927

The Raging Grannies: \nUnderstanding the Role of Activism in the Lives of Older Women

2007· dissertation· en· W7052129927 on OpenAlexaboutno aff

Bibliographic record

VenueUWSpace (University of Waterloo) · 2007
Typedissertation
Languageen
FieldEngineering
TopicElectrostatic Discharge in Electronics
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionCircumstantial evidenceTSG101Context (archaeology)CentenarianHyporeflexia
DOInot available

Abstract

fetched live from OpenAlex

Guided by feminist gerontology, this qualitative study explored the role of activism in the lives of older women. More specifically, it examined the involvement of older women in one particular group of activists, the Raging Grannies. Of particular interest was to understand the experience of how and why older women become involved in activism. This study was collaborative in nature, with in-depth active interviews as the primary method of data collection. In total 15 women participated in face-to-face interviews, with five women contributing to the study in an on-line Raging Grannies forum. Participants were located in Ontario, New Brunswick, and Nova Scotia. The findings demonstrated that these women, who used non-violent, creative methods of protest, challenged the traditional views of growing older. Through their activism, the Raging Grannies also created community. Although the Raging Grannies did not define their experience as leisure, they described their experience as "fun" but rewarding work. The intent of this research was to contribute to the literature on ageing and leisure while giving the opportunity for older women to share their stories. Emergent theory suggests that activism for these women represented the application or expression of shared life experiences which are unique to women. The Raging Grannies provided the space for the study participants to express their collective life experiences, particularly in the context of shared concerns around a more just, fair and sustainable society.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.868

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.005
GPT teacher head0.196
Teacher spread0.191 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

Explore more

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