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Enregistrement W3015898625 · doi:10.1353/aim.2020.0002

"You can never replace the caribou": Inuit Experiences of Ecological Grief from Caribou Declines

2020· article· en· W3015898625 sur OpenAlexaboutno aff
Ashlee Cunsolo, David Borish, Sherilee L. Harper, Jamie Snook, Inez Shiwak, Michele M. Wood, The Herd Caribou Project Steering C

Notice bibliographique

RevueAmerican imago · 2020
Typearticle
Langueen
DomaineHealth Professions
ThématiqueIndigenous Studies and Ecology
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésThreatened speciesMainstreamExtinction (optical mineralogy)BiodiversityEnvironmental changeClimate changeGriefGeographyEcologyEcosystem servicesEcosystemEnvironmental ethicsEnvironmental resource managementPsychologyPolitical scienceEnvironmental scienceBiology

Résumé

récupéré en direct d'OpenAlex

"You can never replace the caribou":Inuit Experiences of Ecological Grief from Caribou Declines Ashlee Cunsolo (bio), David Borish (bio), Sherilee L. Harper (bio), Jamie Snook (bio), Inez Shiwak (bio), Michele Wood (bio), and The Herd Caribou Project Steering Committee (bio) Introduction We are living in a time characterized by ongoing and accelerating ecological loss. Indeed, with recent reports from the United Nations Intergovernmental Science-Policy Platform on Biodiversity and Ecosystems Services (IPBES) Global Assessment (2019) identifying unprecedented species declines and accelerating extinction rates with 1 million species threatened with extinction, and the Intergovernmental Panel on Climate Change (IPCC) Special Report on Global Warming of 1.5°C (2018) calling for "rapid, far-reaching, and unprecedented changes" in society, it is clear that now is a time of great environmental upheaval, loss, and change, with resulting effects on human emotions and mental wellness ("Focus on climate change and mental health," 2018). The already-present, worsening, and projected environmental stressors and experiences (IPBES, 2019; IPCC, 2018, 2019) are creating the need for new understandings and new [End Page 31] lexicons—understandings and lexicons that reflect the full range of our emotional relationships with the land, ecosystems, and the more-than-human worlds. With eco-emotional terms such as solastalgia (Albrecht et al., 2007), biophilia (Fromm, 1973; Wilson, 1984), topophilia (Tuan, 1974), and other types of psychoterratic syndromes (Albrecht, 2019) entering both the research and mainstream lexicons, it is clear that new concepts are needed to identify, understand, and communicate how the loss of environments, ecosystems, and species globally is associated with emotional pain, psychological distress, and anxiety (Albrecht, 2019; Cunsolo & Ellis, 2018; Cunsolo & Landman, 2017a). One such concept that is gaining continued traction in research, professional practice, policy, and general public interest is "ecological grief" (Cunsolo & Ellis, 2018; cf. Albrecht, 2019; Clayton, Manning, Krygsman, et al., 2017; Cunsolo & Landman, 2017a; Minor et al., 2019). Ecological grief, or the "grief felt in relation to experienced or anticipated ecological losses, including the loss of species, ecosystems and meaningful landscapes due to acute or chronic environmental change" (Cunsolo & Ellis, 2018, p. 275), is a natural human response to ecological degradation or destruction. Global research has documented ecological grief related to: warming temperatures and resulting sea ice loss and environmental alterations in Northern and Arctic regions (Clayton et al., 2017; Cunsolo Willox et al., 2012; Cunsolo Willox, Harper, Edge, et al., 2013a; Cunsolo Willox, Harper, Ford, et al., 2013b; Durkalec, Furgal, Skinner, & Sheldon, 2015; Minor et al., 2019); long-term drought and agricultural land loss in the Wheatbelt in Australia (Ellis & Albrecht, 2017); forest fires, and the resulting destruction of home and place, often leading to displacement in the Northwest Territories, Canada (Dodd et al., 2018); the decline of sparrows in urban landscapes in the United Kingdom (Whale & Ginn, 2017); the disappearance of culturally-significant plants in ecosystems in Australia (Ryan, 2017); and the loss and degradation of wild soundscapes (Krause, 2017). Ecological grief has also been documented in scientists and ecologists who research climate change and biodiversity loss (Clayton, 2018), as well as within stories and testimonies from the general public (cf. Clayton, Manning, Krygsman, & Speiser, 2017; "Is this how you feel," n.d.). [End Page 32] Like other forms of grief, research, published literature, and testimonies of lived experience indicate that ecological grief, if left undiscussed and unsupported, has the potential to cause psychological disruptions and disturbances in one's life and activities. Authors such as Judith Butler (2004) and Ashlee Cunsolo and Karen Landman (2017a), however, have identified the ways in which ecological grief—and what we choose to grieve—illuminates not only our fundamental dependency on healthy and thriving ecosystems, but also the political and ethical responsibilities we have to these systems, and to each other, and opportunities for action and healing. Butler (2004), for example, argues that grief and mourning carry a "we-creating" capacity, at once exposing our deep and often-unacknowledged connections to others (human or non-human) and reminding ourselves of our responsibilities to mitigate human-induced environmental destruction and degradation. Building on this diverse and growing body of literature on ecological grief and loss, this article characterizes the lived experiences of loss and grief experienced by...

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)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies, Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: Qualitatif
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,070
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0020,001
Communication savante0,0000,000
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 Opus0,037
Tête enseignante GPT0,354
Écart entre enseignants0,317 · 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.

Devis d'étudeQualitatif
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

Citations83
Publié2020
Routes d'admission1
Résumé présentoui

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