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Record W3217741175 · doi:10.32920/ryerson.14656470.v1

A Critical Discourse Analysis on the Framing of the Feminization of Forced Displacement

2021· preprint· en· W3217741175 on OpenAlexaff
Samantha DeBoer

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsWilfrid Laurier UniversityToronto Metropolitan University
FundersUnited Nations High Commissioner for Refugees
KeywordsEssentialismFraming (construction)Gender studiesSociologyCritical discourse analysisDiscourse analysisFeminization (sociology)FeminismDiscursive psychologyPublic discourseBinary oppositionConstruct (python library)Displacement (psychology)EpistemologyPsychologyLinguisticsPoliticsPolitical sciencePsychoanalysisIdeologyLaw

Abstract

fetched live from OpenAlex

The Major Research Paper seeks to examine the discursive practices that frame the issue of the feminization of forced displacement and construct representations of forcibly displaced women. It will examine the discourse that constructs representations of forcibly displaced women, which has implications for their protection and treatment in society. Forcibly displaced women are victimized through the representational discourse in terms of how they are spoken about and their visual depictions (Johnson, 2011). Based on feminist theory, the conceptual framework of the gender binary, gender and cultural essentialism, representations of victims, the discourse of victimization, and global feminism will be applied to a critical discourse analysis of the UHCR Handbook for the Protection of Women and Girls. This paper argues that the linguistic constructs and discursive practice contribute to misrepresentations of forcibly displaced women.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.012
Threshold uncertainty score0.088

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0120.039
Scholarly communication0.0100.010
Open science0.0010.007
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.362
Teacher spread0.339 · 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 source (direct Gemma or distilled Codex), 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
Published2021
Admission routes1
Has abstractyes

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