2. Resumen de las Principales Políticas Contables
2.14 Clasificación de saldos corrientes y no corrientes
Youth unemployment numbers are widely considered particularly problematic, in part because most developing economies have large informal economies. Also, employment numbers do not capture the quality of employment, its full- or part-time status, and whether it is long-term or temporary. The International Labour Organisation has been developing new tools to handle these challenges.
Looking at the 2000-2015 trend, youth unemployment is lower across the Commonwealth with the exception of Very High HDI countries and their overlapping Advanced Economies grouping (see Chart 26 on page 55). Currently, youth unemployment is estimated to stand at 12% in Asia, 22% in the Caribbean, 16% in the Advanced Economies, and 19% in Africa. Across HDI levels, it is 15% in Very High, 17% in High, 26% in Medium, and 12% in Low. However, some countries do not have sufficient data. Krugman (2015) writes in the United States that “there’s no evidence that a skills gap is holding back employment”. King and Palmer (2010: 40) warn education planners about the politics of “skills-for-employment”. They stress that “education, training, and skills development do not produce jobs in the absence of an enabling macro-economic environment”.
High levels of youth unemployment should be read as a problematic macro-economic environment for youth, rather than a problem with education systems. In an analysis of historical Commonwealth socio-economic data, Menefee (2013) found few correlations between more schooling and economic performance indicators, with the exception of literacy rates. There are clearly links between education systems, economic performativity, and problems like youth unemployment, but they are complex and nuanced. Because current socio-economic performativity can not explained by educational performativity, we should question assumptions that place the burden of producing a more equitable, productive, and sustainable future on the shoulders of schools and teachers.
King and Palmer (2010: 51) write that, “more attention should be paid to promoting equitable access, quality training, and an environment in which skills can be productively utilized by the poor (and by the disadvantaged, vulnerable, and marginalized in general).” This attention should be balanced by legitimate concerns that vocational education is second class education for second class citizens. Upper secondary education should embrace diverse, equitable, and modular systems that help students transition from school to adult life.
Teachers
Teacher-pupil ratios were more than twice as high in Low HDI countries than Very High HDI countries, at 22:1 and 10:1 respectively. The estimates show that at 24:1 the ratios were even greater in Medium HDI countries, which have seen some of the strongest gains in expanding enrolment. High HDI countries sat nearer to Very High HDI countries with a ratio of 14:1.
The ratios dropped by between 29% and 39% in most clusterings: Very High HDI (35%), High HDI (29%), Low HDI (37%), Asia (33%), the Caribbean (32%), and the Advanced Economies (35%). Changes were slower in Medium HDI countries (16%),
14 12 26 22 12 16 10 8 21 19 0 5 10 15 20 25 30 35 40 Asia
[7 of 7] Caribbean [5 of 12] Economies Advanced [7 of 7]
Pacific
[2 of 9] Sub-‐Saharan Africa [18 of 18] 2000 2015 12 21 21 27 27 15 15 7 0 5 10 15 20 25 30 35 40 45 Very High
[8 of 8] [7 of 17] High [9 of 12] Medium [15 of 14] Low 2000 2015
Chart 25: Youth Unemployment Rate Averages By Commonwealth Region
(2000-2015)
the Pacific (7%), and Africa (23%). Only nine of 19 African Commonwealth countries have sufficient data for analysis, and the standard deviation (16) and confidence interval (9) make it difficult to talk about ‘averages’.
Upper secondary teacher student ratios are nearly identical in 2015 in Asia, the Pacific, Advanced Economies, Africa, and by Very High HDI level. The ratio is 2.9 points lower in High and Medium HDI countries. Asia, the Caribbean, Very High HDI, and High HDI countries are all seeing significant reductions in the ratio in upper secondary. The Pacific, Africa, Medium HDI, and Low HDI countries are all seeing the ratios grows.
Gender Equity
The Muscat Agreement called for “all girls and boys [to] complete free and compulsory quality basic education of at least 9 years and achieve relevant learning outcomes, with particular attention to gender equality and the most marginalized”. This proposal expanded the meaning of ‘basic education’, and went beyond EFA Goal 2 in calling for universalization of lower secondary education.
Goal 4 of the proposed Sustainable Development Goals is “Ensure inclusive and equitable quality education and promote life-long learning opportunities for all”. Target 4.1 is “by 2030, ensure that all girls and boys complete free, equitable and quality primary and secondary education leading to relevant and effective learning outcomes”. This does not indicate the level of secondary education, so could be interpreted as being even more ambitious.
The Muscat Agreement placed less emphasis on girls’ education than the Dakar EFA goals. In 2000, Goal 5 was: “Eliminating gender disparities in primary and secondary education by 2005, and achieving gender equality in education by 2015, with a focus on ensuring girls’ full and equal access to and achievement in basic education of good quality.” By 2014, when the delegates assembled in Muscat, gender discrimination in enrolment towards girls had become less problematic.
The gender inequality against girls that exists in Commonwealth education in 2015 is found mainly in primary school. Even here, the disparities are not especially troubling (see Chart 27 on page 57). A few percent more boys are enrolled than girls, usually less than 3%. The most inequitable region for girls today is Asia, where the average GPI is .983. A class with 98 girls and 100 boys would produce this GPI.
In lower secondary, no HDI Level or regional averages of Gender Parity Index (GPI) measurements were unfavourable towards girls (i.e. below 1.0). Instead, the issue has become reversed. Very High HDI and Advanced Economy GPIs are the most equitable, at 1.01. In Low and Medium HDI countries, GPIs are inequitable (1.16) and show fewer enrolled boys than there should be. This is also the case in Africa, where the GPI average is 1.2 (see Chart 28 on page 57).
Chart 27: Primary ANER Gender Parity Index (GPI) By Commonwealth
Region (2000-2015)
0.947 0.994 1.009 0.983 0.993 0.983 1.016 1.002 1.011 0.999 0.80 0.85 0.90 0.95 1.00 1.05 1.10 Asia[7 of 7] Caribbean [12 of 12] Economies Advanced [5 of 7]
Pacific
[5 of 9] Sub-‐Saharan Africa [15 of 18] 2000 2015
Chart 28: Lower Secondary ANER Gender Parity Index (GPI) By
Commonwealth Region (2000-2015)
1.015 1.132 1.004 1.077 1.181 1.041 1.095 1.015 1.068 1.200 0.80 0.90 1.00 1.10 1.20 1.30 1.40 1.50 1.60 Asia[7 of 7] Caribbean [11 of 12] Economies Advanced [5 of 7]
Pacific
[6 of 9] Sub-‐Saharan Africa [12 of 18] 2000 2015
The authors made a conscious decision to place learning outcomes in the quality section of the Report Cards rather than in the inequality section, though - like every other metric - there are also clear implications for inequality. Further, a decision was made not to report the learning outcomes data in “League Table” form, because much is lost in averages. As with so much else in this report, multiple numbers are provided rather than a single metric.
The numbers discussed below come from the three most prominent international learning assessments: SACMEQ, TIMSS-PIRLS, and PISA. More information on methodology can be found in the Glossary at the end of this book. SACMEQ focuses on eastern and southern Africa, PISA is mostly conducted in advanced and middle-income economies, and TIMSS-PIRLS is the most widely distributed. Though numbers have different performativity thresholds and underlying methods, all three assessments report the percentages of students scoring above and below the highest and lowest thresholds. The designated threshold levels vary for literacy and numeracy. The cut-off point for lowest threshold literacy levels in Commonwealth countries was 18% for SACMEQ (see Chart 32 on page 61) and 11% for PIRLS (see Chart 33 on page 61). With mathematics the numbers were 32% for SACMEQ, 28% for TIMSS, and 25% for PISA. At the top end for reading, 10% scored the highest threshold in PIRLS and 5% in SACMEQ. At the top end of mathematics, the threshold was 9% for PIRLS, 15% for PISA, and 1.4% for SACMEQ.
Among the assessments, TIMSS 2011 mathematics had the greatest diversity of scores from Commonwealth countries, with Australia, Botswana, Ghana, Malta, Malaysia, Singapore, and New Zealand reporting. Chart 30: Distribution of TIMSS 2011 Maths
Scores (page 59) shows inter-country inequalities. Singapore is a notable outlier in that
46% of pupils taking the assessment scored at the highest performance benchmark. By contrast, fewer than 1% of pupils in Botswana and Ghana were able to achieve the same results. In Malaysia 2% of students reached this level, while Australia, Malta and New Zealand reported 10%, 4% and 5% respectively.
At the other end of the scale, only 1% of Singaporean pupils were at the lowest performance benchmark. Australia, Malta and New Zealand had 11%, 12%, and 16% respectively. In Ghana, four out of five students (79%) scored at the lowest level, and two out of five (40%) did so in Botswana.