Indicator description

This indicator measures the extent to which climate change is included as a component of a country’s technical and vocational education and training (TVET) laws and policies. The MECCE project built a database of official TVET laws and policies and used a keyword analysis of 29 environmental, sustainability, and climate words translated into 11 languages to assess the extent of integration of climate change into a nation’s TVET laws and policies.

Dataset(s) the indicator is based on

The dataset was built by the MECCE team compiling TVET laws and policies from the UNEVOC TVET country profiles and through web searches, SCRIBD and Course Hero. When still no documents could be found for a country, the UNESCO regional offices, the Ministry of Education of the country or other institutions or country experts were contacted.

Documents are public; database created by MECCE

The dataset is in 11 languages (besides English): Arabic, Bulgarian, Dari, French, German, Italian, Polish, Portuguese, Russian, Spanish, Swedish.

Temporal scope

• Time period(s) collected data is available: National law and policy documents were collected from June – September 2022. Documents included in the database were released between 2000 and 2022.
• Frequency of data collection in the past: N/A
• Frequency of data collection in the future: MECCE will update the database yearly.
• Change over time: N/A. .

Sample size, characteristics, and geographical coverage

Total sample: 147 documents (86 laws and 61 policies) from 102 countries.

The selection of countries was based on the availability of TVET laws and policies. Only TVET laws and policies released after 2000 were included. If less than 10 references to 15 Training keywords were found the document was excluded. If at least one policy was found for a country, the policy document was analyzed and additional laws excluded. As a result 50 countries were analyzed based on policies and 52 based on laws. In cases where more than one policy or law was available for a country, the standardized references for all documents were averaged.

Country coverage (out of 197 UNFCCC parties) by SDG grouping. Percentage in brackets corresponds to total number of countries per SDG grouping.

Data Preparations

The MECCE project organized the collected documents and extracted basic metadata including the document name, country, year of publication, and language. The majority of the documents found were in English, followed by Spanish and French. In order to analyze the non-English documents Climate Change and Training keywords were translated into 11 languages. Our translation protocol was:

1) drawing on existing translations, either from previous similar studies or in official UN and EU documents;
2) conducting translations using DeepL. For those languages not covered by DeepL, Google translate was used.
3) Native speakers were contacted to proofread all keywords. They also considered grammatical cases and gender in their translations and added plural forms.

Keyword queries were run using the software Nvivo which provided keyword counts for each of the documents for each keyword (15 Training related, 29 Climate related). These keywords were then summed into one of three categories for each document, Training, Environmental/Sustainability, and Climate Change. The keyword counts for each category were standardized for comparative purposes by dividing by the total words in the document multiplied by one million.

If a country had more than one document, the standardized references were then averaged across all documents for each category. The final database for indicator calculation therefore utilized a standardized reference count for Environmental/Sustainability and for Climate Change keywords for each country.

Indicator Calculations

1: No Keywords found
2: Any Environmental/Sustainability Keywords
3: Fewer than 100 Climate Change Keywords OR High amount of Environmental/Sustainability Keywords (More than 1,000)
4: Between 100 and 1,000 Climate Keywords (Moderate)
5: More than 1,000 Climate Keywords (High)

Limitations

Translation: working with keywords in 11 languages is a complex endeavor. For the languages with noun declensions, we were able to obtain declinations for all.

Acknowledgements

The MECCE Project would like to thank all the translators who supported the keyword translations and the Research Assistants who dedicated endless hours to prepare this indicator.