Identitk of vegan and vegetarian’s social representations and social eating practices through field study, traditional media and web2.0 user-generated content studies in four geo-cultural contexts
Notice bibliographique
Résumé
The study presented in our empirical contribution benefits the interrelated world of education and health, due to the relevant applied implications of formal and informal education (in particular for the genesis and dissemination of social representations through web2.0 user-generated content among young people) as far it concerns new social eating practices, life-style and world’s views. In a world struck by climate change, economic crisis and increasing health issues, veganism and vegetarianism seem to be rapidly growing as phenomena proposing its alternative minority view on how to resolve some of these issues. The two notions can be always more frequently found in the centre of the public debates. The wide media coverage however leaves a divided public opinion, generating hegemonic, emancipated or polemical social representations depending on their degree of shared consensus. Inspired by Moscovici’s Social Representation Theory (1961/1976) [1] and his Active Minorities Theory (1976/1979) [2], the contribution investigates how groups of vegans and vegetarians see themselves as well as how are they being seen by the rest of population and comparing their views, attitudes and foods preferences in individual/social eating contexts in four different geo-cultural context/continents: Italy (Europe), Brazil (South America) and Canada (North America) in China (Asia). Three interrelated research lines inspired by de Rosa’s modelling approach [3] have been developed: a) field studies, administering de Rosa’s associative networks technique [4] [5] [6] and a specifically designed questionnaire (“Social Eating Practices”) to 484 participants, aged 19-55, belonging to 5 different self-declared groups of food-preferences (without food restrictions; meat- lovers; fish-lovers; vegetarians; vegans); b) traditional mass media, analysing on-line editions of the most read newspapers in three countries (Corriere della Sera –Italy, Correio Brazilense –Brazil, Toronto Star- Canada); c) Web2.0 social media analysis, investigating the topic related user-generated contents on Instagram and Twitter. The results indicate major similarities among vegan and vegetarian subjects in all countries, regarding the way they search for information and how they see themselves, but their views on life-style, food and social implications of their preference can be slightly different depending on cultural and economical reality of the country they live in. The level of tolerance of meat eater towards them can variate depending on country, as well as the mass-traditional or social media depiction characterized by top-down or bottom-up information structure: the former representing normative view related to the majority of food preference styles in the respective geo-cultural contexts, the latter as a channel for expressing ‘voices’ also of minority groups like vegans.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,005 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».