Editorial: Discrete emotions in environmental decision-making
Notice bibliographique
Résumé
For the past few decades, emotion research has demonstrated how emotional valence differentially influences individuals' decision making (Peters et al. 2006). However, there is still very limited understanding regarding how discrete emotions can influence environmental behavior, potentially due to the complex nature of climate change (Pihkala 2022). Understanding the role of emotions is vital in this setting as research has demonstrated strong predictive power for outcomes like climate mitigation (Xie et al., 2019), preference for energy technologies (Jobin and Siegrist, 2018), and support for policy (Smith and Leiserowitz, 2014). Environmental decisions often involve complex and multifaceted issues with long-term consequences (Larson et al., 2015), and people's emotional responses can heavily influence their attitudes and actions (Davidson and Kecinski, 2022). Positive emotions like empathy and concern for nature can motivate individuals to engage in pro-environmental behaviors, such as recycling or supporting conservation efforts (Berenguer, 2007). Conversely, negative emotions like fear or denial can hinder environmental action or lead to unsustainable practices (Bostrom et al., 2018). This special issue of Frontiers recognizes the emotional underpinnings of environmental decision-making, policymakers, educators, and advocates can tailor their messages and strategies to appeal to people's emotions in ways that inspire positive environmental actions. The first paper in our special issue, Shipley et al. (2023) focus on two discrete emotions-pride and guilt. The authors how place attachment influence these two discrete emotions, thereby influencing pro-environmental behavior. Then, Sanford et al. (2023) focus on social media-specifically, the authors examine Twitter "tweets" and the emotional content they contain as they relate to environmental awareness. The concern for protecting the planet continues to be examined with Seibt et al. (2023) addressing how communal sharing relationships evoke an emotion termed "kama muta," thereby expanding an understanding of how sympathy, compassion, and care influence environmental decision-making. Myers et al. (2023) then shift focus to communication strategies. Specifically, the authors examine how emotions regarding climate change information (not climate change more generally) influence their support for policy measures, focusing on the five emotions of guilt, anger, hope, fear, and sadness. Recognizing the global scope and complexity of climate concerns, Bohm et al. (2023) use Appraisal Theory to examine cross-cultural differences in emotional reactions to climate change and climate related actions. Zhang et al. (2023) also bring an international scope studying how adolescents' happiness may influence their willingness to protect the environment using data from eight countries. Our penultimate article, Geiger et al. ( 2023) use meta-analysis to investigate the effectiveness of hope in promoting sustainable decisions.Future research on the role of individuals' emotions in environmental decision-making should further explore how emotional responses vary across different environmental issues and contexts beyond culture (Bohm et al., 2023) and age (Zhang et al., 2023). Investigating whether emotions differ in intensity and directionality depending on the type of environmental concern (e.g., climate change, deforestation, pollution) and the geographic, cultural, or socio-economic context in which individuals are situated can provide valuable insights for tailoring communication and policy approaches.Understanding the nuanced emotional landscape surrounding diverse environmental challenges can inform targeted interventions that resonate with individuals' emotional realities, fostering more profound connections to nature and driving meaningful pro-environmental actions. Additionally, research could delve into the interplay between emotions and cognitive processes in online environments as communication these days are largely done using social media (Sanford et al., 2023). Ultimately, these investigations can empower policymakers, educators, and activists to effectively harness emotions as a force for positive environmental change. Indeed, recognizing emotions not toward climate change itself but toward communication (Myers et al., 2023) will further expand how emotions play a role in sustainable decision-making. Policy-makers can design incentives and rewards that trigger positive emotions for adopting eco-friendly behaviors, reinforcing the link between personal well-being and environmental responsibility. Finally, new methods such as meta-analyses (Geiger et al., 2023) can better assess the effectiveness of strategies and interventions beyond traditional psychological methods of surveys and experiments. Indeed, policy-makers can strategically leverage people's emotions to promote environmentally friendly choices and decisions by employing targeted communication and policy interventions, as Myers et al. ( 2023) has shown. By crafting compelling narratives that evoke empathy and concern for the environment, policy makers can raise awareness about pressing environmental issues and their potential impact on communities and future generations. Utilizing positive emotional appeals, such as hope and optimism (Myers et al., 2023), or guilt, pride and even sympathy (Shipley et al., 2023;Seibt et al., 2023) policy makers can highlight success stories and the transformative potential of sustainable practices, inspiring individuals to take action. By tapping into the emotional dimensions of decision-making, policy makers can foster a sense of shared responsibility and collective action, empowering individuals to become agents of positive environmental change.
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 | 0,006 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,004 | 0,001 |
| Méta-épidémiologie (sens large) | 0,004 | 0,004 |
| Bibliométrie | 0,004 | 0,002 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,011 | 0,006 |
| Science ouverte | 0,006 | 0,003 |
| Intégrité de la recherche | 0,018 | 0,020 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,032 | 0,017 |
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 ».