Social Science Research/Human Activities as a Cause of Climate Change

Social Science Research Human Activities as a Cause of Climate Change Statistics on Religion Well-being in city The source https://pmc.ncbi.nlm.nih.gov/articles/PMC11445540, titled "The International Climate Psychology Collaboration: Climate change-related data collected from 63 countries," describes an international study on the psychology of climate change, involving 59,508 participants from 63 countries. The study, conducted between July 2022 and July 2023, addresses the need to better understand the psychology of climate change, including people's various beliefs, their support for climate policies, and their willingness to act at the individual level across countries. It consisted of subjects completing a multiple-choice questionnaire. The dataset with participant responses can be downloaded from OSF here: https://osf.io/ytf89/files/osfstorage. The variables from the questionnaire administered to respondents, which will be examined in this report, are: "age" (Age), education (Education.2 with the values ​​primary, secondary, tertiary, doctorate/master, no answer), political orientation (Politics2_1 with a value between 0 and 100 with high values ​​of right, low values ​​of left, medium values ​​of center) and the answer to the question: "How accurate do you think this statement is? "Human activities are causing climate change" (Belief.in.CC_1 with a value between 0 and 100). Education People with tertiary education (bachelor's degree) or a doctorate/master's degree are more likely to believe that human activities are causing climate change, but 4.66% of graduates in the sample and 4.13% of those with doctorates do not believe this! #Loading data and libraries library(dplyr) data_notimers <- read.csv("data_notimers.csv") data_notimers$Education.2 <- factor(data_notimers$Education.2, levels = c(1,2,3,4,5), labels = c("Primary","Secondary","Tertiary","Doctorate/Master's","No answer")) df <- data_notimers[-which(is.na(data_notimers$Education.2)),] df %>% group_by(Education.2) %>% summarise(media=mean(Belief.in.CC_1, na.rm=TRUE)) %>% arrange(desc(average)) Education.2 media 1 Terziaria 79.0 2 Dottorato/Master 78.5 3 Primaria 78.3 4 Secondaria 76.0 5 No risposta 71.3 df2<-data_notimers %>% filter(Education.2=="Tertiary") out<-boxplot(df2$Belief.in.CC_1, plot = FALSE)$out round(length(out)*100/nrow(df2),2) [1] 4.66 Political Orientation Left-wingers are more likely to believe that human activities are causing climate change, but 7.3% of the sample doesn't believe it, along with 4.29% of right-wingers! politics <- rep(NA,nrow(data_notimers)) politics[data_notimers$Politics2_1>=70] <-"Right" politics[data_notimers$Politics2_1>35 & data_notimers$Politics2_1<70] <-"Center" politics[data_notimers$Politics2_1<=35] <-"Left" data_notimers$politics <- politics df <- data_notimers[-which(is.na(data_notimers$policy)),] df %>% group_by(policy) %>% summarise(media=mean(Belief.in.CC_1, na.rm=TRUE)) %>% arrange(desc(average)) media politics 1 Left 85.2 2 Center 75.7 3 Right 75.1 df2<-data_notimers %>% filter(politics=="Left") out<-boxplot(df2$Belief.in.CC_1, plot = FALSE)$out round(length(out)*100/nrow(df2),2) [1] 7.3 Age As we grow up As age increases, the number of respondents who believe climate change is caused by human activities decreases. age_group <- rep(NA,nrow(data_notimers)) age_group[data_notimers$Age>=51] <-"High Age" age_group[data_notimers$Age>25 & data_notimers$Age<51] <-"Medium Age" age_group[data_notimers$Age<=25] <-"Low Age" data_notimers$age_group <- age_group df <- data_notimers[-which(is.na(data_notimers$age_group)),] df %>% group_by(age_group) %>% summarise(media=mean(Belief.in.CC_1, na.rm=TRUE)) %>% arrange(desc(media) age_group media 1 Low Age 82.4 2 Medium Age 78.1 3 High Age 73.5 Differences between States The US ranks last in the sample in holding humans responsible for climate change. df %>% group_by(country) %>% summarise(media=mean(Belief.in.CC_1, na.rm=TRUE)) %>% arrange(desc(media) country media 1 philippines 92.3 2 portugal 92.2 3 tanzania 92.1 4 ghana 90.4 5 kenya 89.0 6 uganda 88.7 7 turkey 88.2 8 srilanka 88.1 9 uruguay 88.1 10 chile 87.9 11 brazil 87.1 12 mexico 86.8 13 gambia 86.5 14 india 86.2 15 china 86.0 16 vietnam 85.1 17 nigeria 85.0 18 italy 84.9 19 peru 84.6 20 ecuador 84.2 21 canada 84.2 22 armenia 83.4 23 czechia 83.3 24 ukraine 83.2 25 southafrica 82.6 26 serbia 82.2 27 romania 82.1 28 venezuela 81.5 29 northmacedonia 81.4 30 southkorea 80.8 31 algeria 80.7 32 spain 80.7 33 ireland 80.5 34 singapore 80.5 35 taiwan 80.0 36 thailand 79.8 37 bulgaria 79.6 38 france 78.9 39 switzerland 78.3 40 morocco 78.2 41 poland 77.9 42 uk 77.6 43 unitedarabemirates 77.0 44 sudan 76.3 45 russia 76.2 46 greece 76.2 47 slovenia 75.7 48 finland 75.6 49 netherlands 75.6 50 australia 75.2 51 germany 74.8 52 denmark 74.1 53 japan 73.9 54 sweden 73.8 55 newzealand 73.6 56 latvia 73.3 57 austria 73.2 58 slovakia 73.1 59 belgium 72.9 60 israel 72.0 61 norway 71.1 62 usa 69.6 63 saudiarabia 69.5