Algorithm Applied to SDG13: A Case Study of Ibero-American Countries
Abstract
:1. Introduction
2. Materials and Methods
2.1. Literature Review
2.1.1. Climate Change
2.1.2. OWA Operator
2.1.3. Climate Change and OWA Operator
2.2. Research Sample
2.3. Methodology
2.4. Variables and Measures
2.5. Collection of Official Data for SDG13
2.6. Application of the OWA Operator to SDG13
3. Results Applying OWA Operator to SDG13
4. Discussion of the Results
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
Targets | SDG13 Indicators |
---|---|
13.1 Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries. | 13.1.1 Number of deaths, missing persons, and people directly affected by disasters per 100,000 people. a. Deaths—Exposure to forces of nature—Sex: Both—Age: All Ages (Rate). b. Number of deaths and missing persons attributed to disasters per 100,000 population. c. Internally displaced persons, new displacement associated with disasters. d. Number of directly affected persons attributed to disasters per 100,000 population. |
13.1.2 Score of adopting and implementing local disaster risk reduction strategies in line with the Sendai Framework for Disaster Risk Reduction 2015–2030. 13.1.3 Number of local governments adopting and implementing local disaster risk reduction strategies in line with the national strategy. | |
13.2 Integrate climate change measures into national policies, strategies, and planning. | 13.2.1 Number of countries report establishing or implementing an integrated policy/strategy/plan that enhances their adaptive capacity to the adverse impacts of climate change and promotes climate resilience and low greenhouse gas emissions development. 13.2.2—Total emissions of greenhouse gases per year. |
13.3 Improve education, awareness-raising, and human and institutional capacity on climate change mitigation, adaptation, impact reduction, and early warning. | 13.3.1 Number of countries that have integrated mitigation, adaptation, impact reduction, and early warning into primary, secondary, and higher education curricula. a. Extent to which global citizenship education and education for sustainable development are mainstreamed in curricula. b. Extent to which global citizenship education and education for sustainable development are mainstreamed in national education policies. c. Extent to which global citizenship education and education for sustainable development are mainstreamed in student assessment. d. Extent to which global citizenship education and education for sustainable development are mainstreamed in teacher education. |
Adequacy Level | Evaluation |
---|---|
Null | 0 |
Practically null | 0.1 |
Almost weak | 0.2 |
Very weak | 0.3 |
Weak | 0.4 |
Intermediate | 0.5 |
Fair | 0.6 |
Considerable | 0.7 |
Strong | 0.8 |
Very strong | 0.9 |
Absolute | 1 |
Indicator/ Countries | C1 | C2 | C3 | C4 | C5 | C6 | C7 | C8 | C9 | C10 |
---|---|---|---|---|---|---|---|---|---|---|
a. | 1 | 0.9 | 0.8 | 0.85 | 0.7 | 0.6 | 1 | 0.2 | 1 | 1 |
b. | 0 | 0 | 1 | 0.9 | 0 | 0.3 | 0.95 | 0.85 | 0.2 | 0 |
c. | 0.89 | 0.2 | 0.9 | 0.6 | 0.1 | 0.94 | 0.5 | 0.8 | 0.98 | 0.82 |
d. | 0.9 | 0 | 1 | 0.65 | 0 | 1 | 0.85 | 0.3 | 0.1 | 0 |
Total | 0.6975 | 0.275 | 0.925 | 0.75 | 0.2 | 0.71 | 0.825 | 0.5375 | 0.57 | 0.455 |
Indicator/ Countries | C1 | C2 | C3 | C4 | C5 | C6 | C7 | C8 | C9 | C10 |
---|---|---|---|---|---|---|---|---|---|---|
a. | 0 | 0.94 | 0 | 0.88 | 1 | 0 | 0 | 0.81 | 0 | 0.91 |
b. | 0 | 1 | 0 | 1 | 1 | 0 | 0.75 | 1 | 0 | 1 |
c. | 0 | 0.92 | 0 | 1 | 1 | 0 | 1 | 1 | 0 | 1 |
d. | 0 | 1 | 0 | 0.85 | 0.95 | 0 | 0.8 | 0.2 | 0 | 0.95 |
Total | 0 | 0.965 | 0 | 0.9325 | 0.9875 | 0 | 0.6375 | 0.7525 | 0 | 0.965 |
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Weights | W1 | W2 | W3 | W4 | W5 | W6 |
---|---|---|---|---|---|---|
W= | 0.05 | 0.10 | 0.10 | 0.25 | 0.45 | 0.05 |
SDG13 Indicators | 13.1.1 | 13.1.2 | 13.1.3 | 13.2.1 | 13.2.2 | 13.3.1 |
SDG13 Indicators | |||||||
---|---|---|---|---|---|---|---|
Code | Countries | 13.1.1 | 13.1.2 | 13.1.3 | 13.2.1 | 13.2.2 | 13.3.1 |
C1 | Argentina | 0.70 | 0.78 | 0.90 | 1.00 | 0.40 | 0.00 |
C2 | Brazil | 0.28 | 0.80 | 0.75 | 1.00 | 0.10 | 0.97 |
C3 | Chile | 0.93 | 0.90 | 0.55 | 1.00 | 0.65 | 0.00 |
C4 | Colombia | 0.75 | 1.00 | 0.85 | 1.00 | 0.60 | 0.93 |
C5 | Cuba | 0.20 | 0.75 | 0.70 | 1.00 | 0.85 | 0.99 |
C6 | Ecuador | 0.71 | 0.68 | 0.45 | 1.00 | 0.75 | 0.00 |
C7 | Mexico | 0.83 | 0.93 | 0.30 | 1.00 | 0.20 | 0.64 |
C8 | Peru | 0.54 | 1.00 | 1.00 | 1.00 | 0.70 | 0.75 |
C9 | Portugal | 0.57 | 0.90 | 0.50 | 1.00 | 0.80 | 0.00 |
C10 | Spain | 0.46 | 1.00 | 0.80 | 1.00 | 0.45 | 0.97 |
Code | Countries | OWA | Position |
---|---|---|---|
C1 | Argentina | 0.5730 | 7° |
C2 | Brazil | 0.5455 | 9° |
C3 | Chile | 0.6430 | 5° |
C4 | Colombia | 0.8230 | 1° |
C5 | Cuba | 0.7465 | 3° |
C6 | Ecuador | 0.5685 | 8° |
C7 | Mexico | 0.5310 | 10° |
C8 | Peru | 0.7795 | 2° |
C9 | Portugal | 0.5875 | 6° |
C10 | Spain | 0.6765 | 4° |
Sets | Scale | Adequacy Level | Countries |
---|---|---|---|
S1 | [0.90; 0.99] | Absolute | |
S2 | [0.90; 0.99] | Very strong | |
S3 | [0.80; 0.89] | Strong | C4 |
S4 | [0.70; 0.79] | Considerable | C8 and C5 |
S5 | [0.60; 0.69] | Fair | C10 and C3 |
S6 | [0.50; 0.59] | Intermediate | C9, C1, C6, C2 and C7 |
S7 | [0.40; 0.49] | Weak | |
S8 | [0.30; 0.39] | Very weak | |
S9 | [0.20; 0.29] | Slightly weak | |
S10 | [0.10; 0.19] | Practically null | |
S11 | [0.00; 0.09] | Null |
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Barcellos-Paula, L.; Gil-Lafuente, A.M.; Castro-Rezende, A. Algorithm Applied to SDG13: A Case Study of Ibero-American Countries. Mathematics 2023, 11, 313. https://doi.org/10.3390/math11020313
Barcellos-Paula L, Gil-Lafuente AM, Castro-Rezende A. Algorithm Applied to SDG13: A Case Study of Ibero-American Countries. Mathematics. 2023; 11(2):313. https://doi.org/10.3390/math11020313
Chicago/Turabian StyleBarcellos-Paula, Luciano, Anna María Gil-Lafuente, and Aline Castro-Rezende. 2023. "Algorithm Applied to SDG13: A Case Study of Ibero-American Countries" Mathematics 11, no. 2: 313. https://doi.org/10.3390/math11020313
APA StyleBarcellos-Paula, L., Gil-Lafuente, A. M., & Castro-Rezende, A. (2023). Algorithm Applied to SDG13: A Case Study of Ibero-American Countries. Mathematics, 11(2), 313. https://doi.org/10.3390/math11020313