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GAINING PERSPECTIVE: WHAT DO AFFECTED PERSONS THINK ABOUT OIL SANDS PROCESS-AFFECTED WATER REMEDIATION USING CONSTRUCTED WETLANDS ENHANCED BY GENOMICS?

2023· dissertation· en· W7019407924 sur OpenAlexfundaboutno aff

Notice bibliographique

RevueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Langueen
DomaineEnvironmental Science
ThématiqueConstructed Wetlands for Wastewater Treatment
Établissements canadiensnon disponible
Organismes subventionnairesCanadian Federation of University Women
Mots-clésEnvironmental remediationOil sandsWetlandContext (archaeology)TailingsConfusion
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Effective oil sands remediation requires integrated and holistic knowledge of the problems and potential solutions that can only be acquired through participation and input from affected persons. Mining of Alberta's oil sands consists of water-intensive processes such as hot water extraction, resulting in large quantities of contaminated oil sands process-affected water (OSPW) stored in tailings ponds that require remediation before release. Hence, as mining projects advance, the need for sound policy and improved methods for remediation and release intensifies. Constructed treatment wetland systems (CTWS) have been identified as a viable remediation option, and genomics can be employed to optimize microbial activity, enhancing remediation efficacy. However, researchers have paid limited attention to the priorities and values held by those affected by OSPW remediation and particularly to CTWS enhanced by genomics. To address this gap, I co-designed and performed this research with affected persons, including Indigenous Peoples, oil and gas industry employees, scientists studying CTWS and genomics, and regulators and policymakers considering OSPW remediation. My sequential mixed-method research used a literature review, media review, and focus groups to examine opinions on CTWS and genomics for OSPW remediation and to build a Q-methodology concourse and Q-set for future research to systematically study participant viewpoints. This study found that affected persons have a wide range of opinions about CTWS and genomics in the context of OSPW remediation. They identified barriers to participating in discussions and decisions about CTWS and genomics, the main ones being confusion around proposed technologies and inadequate communications, which can inform future community engagement processes through recommendations. Some affected persons supported CTWS and genomics when methods were piloted, when they knew CTWS and genomics had been used in other applications, and when they knew research was underway or completed. Conversely, affected persons argued that information about CTWS and genomics is sparse and that there is no evidence that CTWS and genomics will not harm the environment, wildlife, or human health and culture. Novel findings were the conflict between affected persons from regulatory bodies and affected persons in industry around placement and continuity of CTWS after a mine is closed, and affected persons’ assertions that wetlands have a spirit. Cultural Theory’s purpose is to use the typology of five ways of organization to categorize, examine, and critique deliberative quality in engagement with affected persons, noting that the most robust solutions to the most challenging problems emerge when all five solidarities are sought and blended in solution generation. In this study, Cultural Theory’s three active solidarities—individualism, hierarchy, and egalitarianism—were observed, while fatalism and autonomy emerged when some participants considered perspectives others might hold. I witnessed synergies between the solidarities, suggesting a capacity for clumsy solutions that incorporate voices from all concerned; however, solidarities are missing in decision-making around remediation policy for OSPW. More research is needed, particularly with local communities, to capture and explore the perspectives of those significantly affected by OSPW remediation. These affected persons could pursue the goals of maximizing accessibility of information and conversations as well as responsiveness to each other’s concerns to enhance deliberative quality and implement robust solutions.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,011
score de la tête « metaresearch » (Gemma)0,019
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
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 enseignants0,986
Score d'incertitude au seuil0,060

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0110,019
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,001
Études des sciences et des technologies0,0060,006
Communication savante0,0050,005
Science ouverte0,0010,005
Intégrité de la recherche0,0030,005
Charge utile insuffisante (le modèle a refusé de juger)0,0050,001

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 Opus0,005
Tête enseignante GPT0,186
Écart entre enseignants0,181 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
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

Citations0
Publié2023
Routes d'admission2
Résumé présentoui

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