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Conservation²: The relationship between Kala language conservation and marine conservation in coastal Papua New Guinea

2015· other· en· W6980693507 sur OpenAlexaboutno aff

Notice bibliographique

RevueThe COCOON platform (University of Paris) · 2015
Typeother
Langueen
DomaineBusiness, Management and Accounting
ThématiqueConsumer Behavior in Brand Consumption and Identification
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésFishingDocumentationSustainabilityPidginNew guineaMarine conservation
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

In this paper we describe a collaboration among anthropologists, marine biologists and the Kala Language Committee in support of the combined goals of language revitalization, marine conservation and development of Kala elementary school curriculum. The Kala language, with four distinct dialects, is spoken in six coastal villages of Morobe Province, Papua New Guinea, where marine resources provide residents with the overwhelming majority of their dietary protein. In 2006, due to concerns about language shift, Kala speakers developed the Kala Language Committee (KLC). The KLC’s goals were to promote Kala rather than acquiesce to Melanesian pidgin (Tok Pisin), the national lingua franca, and English, the national language of education. A related goal was the documentation of Kala environmental knowledge because Tok Pisin, unlike Kala, uses general categories of description rather than words that convey specific information (e.g., species, sex, and age of animals). \n \n Concurrently with the language project, marine conservation research began in the Kala-speaking village of Kamiali. Primary goals were to document marine biodiversity, suggest ways to sustainably manage marine resources, and develop tools to help village residents evaluate the sustainability of their fishing practices. An early hurdle to information transfer to village residents was that no written language efficiently conveyed which species were under discussion; scientific names were overwhelming, whereas common English or Tok Pisin names were ambiguous. The problem was resolved in 2010 when the KLC developed and adopted a Kala orthography. The writing system permitted documentation of Kala fish names, which were subsequently used in publications and educational materials which serve to increase local comprehension of marine-conservation research and guidelines. Continued marine conservation research resulted in the development of a poster with sustainable fishing suggestions and a school curriculum for community-based marine-resource monitoring, which were fully translated into Kala. \n \n We argue that the attention paid to the Kala language via the KLC’s efforts has led to increased awareness of marine diversity and the importance of conservation, as well as to increased awareness of the etymology of Kala terms and associated cultural knowledge. Therefore, building on recent literature about the benefits of collaborative approaches to both language documentation and in situ biodiversity conservation, we argue here for the benefits of engaging with community members in projects that simultaneously document linguistic and ecological knowledge. As well, we argue that integrating the academic disciplines of linguistic anthropology, ecological anthropology and conservation biology can lead to better biolinguistic diversity conservation practices.\n \n References: \n \n Ban, Natalie, Chris Picard & Amanda Vincent. 2009. Comparing and integrating commu¬nity-based and science-based approaches to prioritizing marine areas for protection. Conservation Biology 23. 899–910\n \n Cinner, Joshua E., Michael J. Marnane, & Tim R. McClanahan. 2005. Conservation and Community Benefits from Traditional Coral Reef Management at Ahus Island, Papua New Guinea. Conservation Biology. 19. 1714-1723. \n \n Czaykowska-Higgins, Ewa. 2009. Research models, community engagement, and linguistic fieldwork: Reflections on working within Canadian indigenous communities. Language Documentation & Conservation 3(1). 15-50. \n \n Drew, Joshua & Adam Henne. 2006. Conservation biology and traditional ecological knowledge: Integrating academic disciplines for better conservation practice. Ecology and Society 11. 34–42.\n \n Grenoble, Lenore A. 2010. Language documentation and field linguistics: The state of the field. In Lenore A. Grenoble and N. Louanna Furbee (eds.) Language documentation:Practice and values, 289-309. Amsterdam: John Benjamins\n \n Guérin, Valérie and Sébastian Lacrampe. 2010. Trust me, I am a linguist! Building partnerships in the field. Language Documentation & Conservation 4. 22-33. \n \n Maffi, Luisa (ed.). 2001. On Biocultural Diversity: Linking language, knowledge and the environment. Washington: Smithsonian Institution Press.\n \n Ramstad, Kristina, N.J Nelson, G. Paine, D. Beech, A. Paul, P. Paul, F.W. Allendorf & C.H. Daugherty. 2007. Species and cultural conservation in New Zealand: Maori traditional ecological knowledge of Tuatara. Conservation Biology 21. 455–464.\n \n Si, Aung. 2011. Biology in Language Documentation. Language Documentation and Conservation 5. 169-186.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,306
Score d'incertitude au seuil0,956

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,068
Tête enseignante GPT0,248
Écart entre enseignants0,179 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission1
Résumé présentoui

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