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Record W3116760792 · doi:10.11575/prism/38479

Gender Mainstreaming in Canadian Human Security Policy: The Limitations of Bureaucratic and Security Discourses

2008· article· en· W3116760792 on OpenAlexaboutno aff
Shelina Ali

Bibliographic record

VenuePRISM (University of Calgary) · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Security, and Conflict
Canadian institutionsnot available
Fundersnot available
KeywordsHuman securityBureaucracyGender mainstreamingMainstreamingPolitical scienceCritical security studiesSecurity studiesPublic administrationSociologyGender equalityGender studiesPoliticsNetwork security policyLawCloud computing security

Abstract

fetched live from OpenAlex

The purpose of this study is to assess how feminist literature on bureaucratic discourse and human security can contribute to a greater understanding of the challenges of gender mainstreaming within policy on human security and conflict management. My particular focus on gender is linked to the reality that gender power relations are consistently present within all societies internationally, most often resulting in the subordination of femininity and by consequence, women. Feminist critiques of the bureaucracy make a strong argument for why there is such difficulty in establishing a gendered security policy, by addressing the gender biased nature of bureaucratic structure, knowledge, and discourse. Through the analysis I hope to shed light on the barriers and access points available within the Canadian bureaucracy in terms of gender mainstreaming in human security policy. Past studies have focused on what gendered aspect of conflict and security policy have ignored, but not why they have ignored these aspects. This paper will attempt to further uncover the why, and what feminist theory can contribute towards understanding the difficulty of gender mainstreaming in Canadian human security policy.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.737
Threshold uncertainty score0.762

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.042
GPT teacher head0.259
Teacher spread0.218 · 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 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

Citations0
Published2008
Admission routes1
Has abstractyes

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