Marta Klanjšek Gunde and Mojca Dušica Zajc
National Institute of Chemistry, Ljubljana, Slovenia (Current address of Mojca Dušica Zajc: ABC Accelerator, Slovenia)
Contact: marta.k.gunde@ki.si
Climate change mitigation: gender aspects
Authors
Abstract
Social, economic and political barriers disadvantage women in coping with the adverse effects of climate change. However, women’s extensive knowledge and expertise on livelihood strategies can be beneficial in climate change mitigation, disaster reduction and adaptation strategies. Thus, every mitigation action needs women. Majority of these assertions were based on the data obtained in least developed countries with uneven distribution of wealth and large cultural differentiation between men and women. To verify the validity of the claim that climate change affects women and men differently also in more developed countries, a small social group in Slovenia, consisting of National Institute of Chemistry employees, was asked about their attitudes and behaviours towards climate change. The results are presented using descriptive statistics and correlation coefficient. This way the correlation was obtained between gender/gender-related behaviour and behavioural characteristic that are important in mitigation of climate changes in a small academic social group working at National Institute of Chemistry in Ljubljana, Slovenia (NIC).
Aims: To verify the validity of the claim that climate change affects women and men differently also in more developed countries.
Methodologies: Internet survey was made asking the respondents about their behaviours and attitudes to climate change and its mitigation. The obtained data were correlated to demographic data including gender, age, education type and level, living area. In addition, the possible active participation in a research, innovation, or policies and measures somehow related to climate changes was also included. This way the gender- and other aspects of climate change mitigation were assessed.
The survey was conducted on the Internet using Google Forms questionnaire. It was prepared in Slovenian and English language due to approximately 12 % share of non-Slovenian speakers in the NIC employees. The questionnaire was open from February to April 2019. In the period May – August 2019, the data was joined, cleaned and analysed using MS Excel. We have conducted basic cross-tabulations and have investigated potential correlations between variables.
The survey consisted of three sets of questions:
- Demography – basic information of the respondent – gender as the main variable, age, living area – urban, suburban or rural, level of education, type of education – natural (STEMM) or social-sciences oriented (SSHA), and respondents’ participation in research / innovation / policy connected with climate change (CC). With type of education we wanted to test the informal hypothesis that natural sciences background is positively correlated with agreeing that climate is changing due to human activity which also contributes to active participation in mitigation actions.
- Core attitudes – also called “the Trump questions” – used to assess the attitude of the responders (agree, level of information, worry about, and the level of personal responsibility felt for CC). The answers were used as claims for personal threatening about CC.
- Everyday life behaviours (transport, household work and responsibilities, personal readiness for contribution in mitigation measures that might be small in themselves but can contribute to a large overall impact) – evaluates the way in which the respondents act or conducts themselves in common life situations contributing to mitigation of CC.
The results from demography section were used as one of two variables for calculation the Pearson correlation coefficient; for the second variable, one the attitudes (“Trump questions”) and everyday life answers were applied. This way correlation of the linkage between the responders (described by their demographic variables) and CC and the in the tested community were evaluated.
Gendered results: Climate change is commonly regarded as highly connected to gender, but majority of these data originates from least developed countries with uneven distribution of wealth and large cultural differentiation between men and women. The validity of the claim that climate change affects women and men differently also in our small academic society was evaluated. For this purpose, the internet survey was made with reasonably high response rate and distribution among gender, age, and education. The attitude of the respondents to climate change was regarded together with their everyday life behaviours to evaluate the common life situations that might contribute to mitigation of climate changes.
The results show a low correlation of gender with some household activities and transportation. The connection with household activities likely shows a presence of some still-remaining traditional roles of gender whereas the correlation of gender with transportation might confirm the important role of gender in climate change mitigation.
Gender is correlated with household food clearing, household food preparation, readiness to cease using disposal nappies and to change the transport mode. The first three variables are manifestation of the conventional role of gender which is apparently still found in everyday life, but the correlation is low. The forth variable (transport mode) likely confirm that gender-related roles might be important in climate change mitigation also in the tested community.
Only a weak correlation of gender and some household activities and mode of transportation were obtained. This casts a preliminary doubt on the assertions that climate change affects genders differently.
Introduction
The results from demography section of the survey were used as one of two variables for calculation the Pearson correlation coefficient (PCC); for the second variable, one the attitudes (“Trump questions”) and everyday life answers were applied. This way correlation of the linkage between the responders (described by their demographic variables) and CC and the in the tested community were evaluated.
The PCC measure linear correlation between the variables A and B and could be between -1 and 1. PCC=1 confirms the existence of a linear equation between both A and B, where all data points coincide if A and B increases. If PCC= −1, all data points are on a line for which B decreases if A increases. PCC=0 implies no linear correlation between A and B. The absolute values of PCC express the level to which the tested variables correlate (in the case of negative values it is anti-correlation) which is commonly described in the steps given in Table 1. For our purpose, we take attention to the combinations that give at least low correlation, which is PCC of at least 0.2.
Structure of the respondents
Responses of 127 persons were obtained, which is 38,5 % of all employee at NIC. Out of them, 49 were men, 77 women and 1 person that did not want to define its gender. The response of this person was not included in further analysis. The largest group was below 30 years, the smallest number of men was in the group 40-49, and of women above 60. In the following, men and women opinions were analysed in percentage relative to all men/women participants. Most responders (above 55 %) live in town, whereas countryside and suburb are nearly equally populated. Little more women are living in suburb, but the differences among genders are not significant (Figure 1).
Above 80 % responders have STEMM education, but persons with SSHA and interdisciplinary education also responded our survey. Persons with education levels 7 (finished university) and 9 (master or PhD of science) highly prevail, with level 7 little more frequent for women and level 9 for men (Figure 2).
More than 60 % responders were not involved in research, innovation, or policies and measures, related to CC, which shows that such projects are still rare. Only small differences were obtained on these questions by different genders (Figure 3).
Questions
The “Trump questions” evaluate the personal attitude of responders to CC (Table 2) and were regarded to have no influences on the rest of the survey (variable B in PCC evaluation). The personal agreement with the statement that the climate is changing due to human activity (Table 2, 1st question) was also used as variable A and added to describe the structure of the responders.
The last section of the survey considers everyday life, asking for the type of transport, household work and responsibilities, and personal readiness to contribute in mitigations (Table 3). These life situations were regarded to assess how much the responders are contributing, or willing to contribute, and if there is any correlation of these answers with the responder’s general data.
Correlations between demographic data and other attitudes and lifestyle
The correlations between variables A and B are analysed, which requires PCC values above 0.2. Variable A consists of gender, age, living area, education level, education field, CC research, CC innovation, and CC policies, however, only the first four examples give PCC above 0.2. The added variable “CC personal” (Table 2, 1st question) correlates with “CC worry” (Table 2, 3rd question), giving PCC=0.254 (shown in Figure 4).
Only low correlation was obtained between some of the tested variables (PCC from 0.20 to 0.39) with only one exception – “Living area” in combination with “Household own food” gives PCC=0.4, which is the bottom value for the medium correlation.
In our survey, gender is correlated with household food clearing, household food preparation, readiness to cease using disposal nappies and to change the transport mode. The first three variables are manifestation of the conventional role of gender which is apparently still found in everyday life, but the correlation is low. The forth variable (transport mode) likely confirm that gender-related roles might be important in climate change mitigation also in the tested community.
Conclusion
The internet survey was made among employees of our Institute, which is dedicated to research in the field of chemistry and chemistry-related disciplines. The survey had reasonably high attendance and distribution among gender, age, and education. The attitude of the responders to climate change was regarded together with their everyday life behaviours to evaluate the common life situations that might contribute to mitigation of climate changes. The correlations between the general data of the responders and answers to other questions were evaluated using the Pearson correlation coefficient.
The results show a low correlation of gender with some household activities and transportation. The connection with household activities likely shows a presence of some still-remaining traditional roles of gender whereas the correlation of gender with transportation might confirm the important role of gender in climate change mitigation.
Fact and figures
Table 1: Correlation level of the absolute value of the Pearson correlation coefficient (PCC).
Table 2: The questions and possible answers ranking the relation to the climate change.
Table 3: The questions and possible answers ranking the responder’s everyday life.
Figure 1. The age and gender of the responders (left) and their living area (right).
Figure 3. Participants of the survey (in % respect to all participants) that were included in research, innovation and policies with measures anyhow related to climate change.
Figure 2. The responders according to their type (left) and level (right) of education (in % regarding the corresponding gender group).
Figure 4. Values of Pearson correlation coefficient (PCC) above 0.2 (evidence of at least low correlation) as obtained for variable A (color legend on bottom of the graph) combined with variable B (table legend).
References
Promoting gender balance and inclusion in research, innovation and training (PLOTINA), EU Horizon 2020, Grant Agreement No. 666008.
‘Pocket Guide to Gender Equality under the UNFCCC’, European Capacity Building Initiative (ecbi), October 2017, available at: https://wedo.org/pocket-guide-gender-equality-unfccc/.
‘Overview of linkages between gender and climate change’, Global Gender and Climate Alliance, United Nations Development Programme, 2013, available at: https://www.undp.org/content/dam/undp/library/gender/Gender%20and%20Environment/PB1-AP-Overview-Gender-and-climate-change.pdf.
‘5 Reasons Why Climate Action Needs Women’, United Nations Climate Change, Article / 02 Apr, 2019, available at: https://unfccc.int/news/5-reasons-why-climate-action-needs-women.
‘Invest in Girls and Women to Tackle Climate Change and Conserve the Environment. Facts, Solutions, Case Studies, and Calls to Action’ 10.09.2017. Women Deliver, available at: https://womendeliver.org/wp-content/uploads/2017/09/Deliver_For_Good_Brief_10_09.17.17.pdf .
UNFCCC Topics , ‘Gender’, available at: https://unfccc.int/topics#:70bd5236-db5c-4951-b3f9-f0ba194311f5:ac128401-5857-4a5f-a39c-7c347fc5d06d.
‘The Gender Action Plan’, United Nations Climate Change, available at: https://unfccc.int/topics/gender/workstreams/the-gender-action-plan.
‘The Lima Work Programme on Gender’, United Nations Climate Change, available at: https://unfccc.int/topics/gender/workstreams/the-lima-work-programme-on-gender.
‘Women and climate change’, European Parliament resolution of 20 April 2012 on women and climate change, (2011/2197(INI)), (P7_TA(2012)0145). Available at: http://www.europarl.europa.eu/sides/getDoc.do?pubRef=-//EP//TEXT+TA+P7-TA-2012-0145+0+DOC+XML+V0//EN.
‘Women, Gender Equality and Climate Change’, UN WomenWatch, The UN Internet Gateway on Gender Equality and Empowerment of Women. Available at: https://www.un.org/womenwatch/feature/climate_change/downloads/Women_and_Climate_Change_Factsheet.pdf