Dynamics of prescriptivism and lexical borrowings in Contemporary French
Notice bibliographique
Résumé
In France and Québec, language contact with English is often perceived as a source of negative influence on French. Terminological commissions working under the supervision of the Académie française and the Office québécois de la langue française are tasked to replace foreign words and expressions with French terminology that is mandatory in all government publications. However, the general public is merely encouraged to comply with these recommendations: the actual use of these top-down lexical innovations remains to be established. Using examples from newspaper and social media corpora, this study investigates how speakers comply with the use of prescribed French terminology, including emblematic lexical innovations such as courriel and mot-dièse, rather than their English equivalents.\n\nThe research combines quantitative and qualitative methodologies applied on large corpora of formal and informal written texts from France and Québec. The first quantitative component comprises newspaper articles from 2000 to 2017 in order to examine whether purist recommendations are implemented in formal written language. Time is treated with a new dynamic approach: the probability of use of a prescribed term is estimated three years before and three years after official prescription. 54 target terms are selected from the lexical fields of computer science, entertainment industry and telecommunication. The second quantitative component consists of tweets published from January 2010 to December 2016, targeting 4 lexical items recurring with high frequency in the newspaper corpus. Statistical analyses were implemented on variables of gender (male or female users), social media influence score, and urban population size, complemented with mapping the diffusion of lexical innovations in France and Québec. The third, qualitative component explores reactions to prescription in tweets and newspapers, examined with sentiment analysis and close reading.\n\nThe analyses reveal that prescription is primarily effective when it follows already attested usage, as demonstrated in the estimated probability of use in both the newspaper and the social media corpora. Conservative newspapers show higher proportions of recommended terminology, especially as compared to newspapers specializing in technology. Language users express more prescriptive attitudes in Québec than they do in France, which signals the perception of failed top-down intervention on French social media, but a successful one among Québécois users. These results corroborate previous scholarship on regional variation toward prescription, partly due to English being a prestigious foreign language in France as opposed to a native language in Québec where Francophone speakers showcase stronger linguistic purism against it.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».