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Record W2733765574 · doi:10.1017/s000842391700049x

Finding Feminism(s) in Canadian Political Science Scholarship: Diversity and Resistance in an Era of Global Uncertainty

2017· article· en· W2733765574 on OpenAlexaffabout
Alexandra Dobrowolsky, Fiona MacDonald, Tracey Raney, Cheryl N. Collier, Pascale Dufour

Bibliographic record

VenueCanadian Journal of Political Science · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicGender Politics and Representation
Canadian institutionsUniversité de MontréalUniversity of WindsorToronto Metropolitan UniversityUniversity of the Fraser Valley
Fundersnot available
KeywordsFeminismScholarshipPoliticsDiversity (politics)Political sciencePleasureGender studiesSociologySocial scienceLaw

Abstract

fetched live from OpenAlex

It is with great pleasure that we present this special issue showcasing contemporary feminist political research, theories and practices in Canada. In an era characterized by global movements and numerous transformations that range from the economic to the environmental, the political to the cultural, from macro- through to micro-scales, including complex debates about the fluidity of gender, and where “backlash” against the symbols and agents of past feminist activism is rife, this special issue queries where do we find feminism(s) today? The responses to this question, as well as to the interrogation of the place of gender in the discipline of political science more generally, are undoubtedly diverse and contested. The collective efforts contained in this special issue feature a mere taste of the rich range of thought-provoking recent scholarship on feminisms. And even with this necessarily condensed portrayal (the articles in this issue are shorter than is normally the case to allow for more work to be featured), the special issue is ground-breaking in that it marks the first time the Canadian Journal of Political Science/Revue canadienne de science politique has dedicated an entire issue to topics of gender and feminisms.

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)0.006
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.008
Scholarly communication0.0000.001
Open science0.0020.000
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 head0.063
GPT teacher head0.371
Teacher spread0.308 · 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 designObservational
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

Citations5
Published2017
Admission routes2
Has abstractyes

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