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Record W2340971471 · doi:10.1177/0886109915592667

“Why Are You Talking to Me Like I’m Stupid?”

2015· article· en· W2340971471 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAffilia · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicGender, Feminism, and Media
Canadian institutionsWilfrid Laurier UniversityYork University
Fundersnot available
KeywordsAgency (philosophy)PovertyLimitingInterpersonal communicationSocial psychologySociologyPsychologyGender studiesWelfareQualitative researchDevelopmental psychologyPolitical scienceLawSocial science

Abstract

fetched live from OpenAlex

Based on the analysis of qualitative, semi-structured interviews conducted with 92 welfare-reliant lone mothers living across Canada, this article explores the “micro-aggressions” experienced by these women in their interactions with the social welfare system. Micro-aggressions refer to the verbal and nonverbal, relational exchanges that send denigrating messages to persons of marginalized and discriminated against social groups. From the analysis, we conclude that class and gender become sites, intersecting and interlocking, where micro-aggressions as a form of interpersonal violence and discrimination occur against women/lone mothers living in poverty that act to diminish the agency and sense of public worthiness of these women, in turn limiting their access to contesting these constructions.

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.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.258
Threshold uncertainty score0.803

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.062
GPT teacher head0.326
Teacher spread0.264 · 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