Intersectional Analysis of Perceptions and Attitudes Towards Energy Technologies
Notice bibliographique
Résumé
This document reports on a study of the perceptions and attitudes towards energy technologies undertaken in six case study communities in France, Ireland, Italy, Spain and the United Kingdom. This exploration is conducted as part of a research project exploring the ‘human factor’ in the energy system, within which a complementary study of energy-related practices is also being prepared. Both of these studies are taking an intersectional approach to the analysis, recognising that people have multiple, interdependent, overlapping axes of social identity – this research is focusing on gender, socio-economic privilege and age. The purpose of the report is to move away from the dominating paradigm of treating people as uniquely rational decision-makers and introduce the very real social contexts through which they negotiate and understand their role within the energy system; with specific focus on their views on the energy technologies that comprise it. The underlying feelings, assumptions, associations and values held by the people who express them are very real influencing factors on the attitudes and perceptions of people hold. Subsequently, a report will be produced synthesising these two intersectional analyses along with a range of socio-economic, technical, market and policy analyses from the ENTRUST project. It is intended that this report will be updated over the remaining duration of the project, based on ongoing dialogue with the communities; continued reflexive analysis of the collected data; and insights from complementary outputs (not least those mentioned above) with an updated report envisaged for release in quarter one, 2018. The report is laid out into sections, with each one addressing a specific aspect of the work involved to produce this deliverable. Section 2 outlines the Methodology for this deliverable, exploring the philosophical and theoretical background to the research. It also details the strategies and design processes that guided the selection of specific research methods and techniques used for data collection and analysis. An important contribution to the methodology has been the consideration of ‘intersectionality’, which has enabled the research to move beyond the “single-axis analysis” taken elsewhere. Section 3 provides an overview of the communities comprising a description of each of the six case study communities involved and an outline of their relevance to the research. Section 4 presents the presents the results and findings of the research, and discusses their meaning in the context of the research aims and objectives. The final section concludes the report with a number of key findings that this research suggests contribute towards determining attitudes to specific energy technologies.
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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 | 0,009 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,007 | 0,006 |
| Études des sciences et des technologies | 0,004 | 0,005 |
| Communication savante | 0,009 | 0,005 |
| Science ouverte | 0,001 | 0,008 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 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 ».