MétaCan
Menu
Back to cohort
Record W4406492757 · doi:10.12794/metadc1944207

French and Canadian Inclusive Language Doctrine and Societal Attitudes

2022· dissertation· en· W4406492757 on OpenAlexaboutno aff
Taylor Irene Berthiaume Diaz

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicDiscrimination and Equality Law
Canadian institutionsnot available
FundersAcadémie française
KeywordsDoctrineLinguisticsPolitical scienceSociologyPsychologyPhilosophyLaw

Abstract

fetched live from OpenAlex

One of the most important French grammar rules is the rule of superiority: Masculine subjects always trump feminine subjects when there are multiple subjects. Superiority is closely followed by the acceptance that all nouns have a grammatical gender, either masculine or feminine. Since 1984, and over the span of forty years, these rules have been challenged on multiple levels of French society. The research conducted over the course of this thesis focuses on the mentality and reactions of the French people towards inclusive language made up of inclusive writing campaigns, the feminization of traditionally masculine names, career positions, and titles, and the introduction of gender-neutral forms of conjugating and neo-pronouns. The studied responses are be categorized into those of the French government, the Académie Française, as well as those from the Canadian government and the Office québécois de la langue française. Research demonstrates the existence of a clear division between "traditionalist" and progressive values at work within the afore-mentioned levels of French societal attitudes. While official government publications and committees seem to reflect a positive attitude towards the adoption of feminized terms, the lack of support for inclusive writing systems by the government contradicts this. This thesis outlines these responses and reactions, seeking to establish a timeline for the implementation and acceptance of feminized terms and neutralization efforts in both the French and Canadian governments.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.549
Threshold uncertainty score0.996

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.016
GPT teacher head0.378
Teacher spread0.362 · 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.

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
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicDiscrimination and Equality LawFrench-language works237,207