#DHH21 theme: Exploration of Society Through the Lens of Labour Market Related Documentation

Overtime and Annual Leave

It is clear that the current results do not seem to represent a perfect situation. As shown in the graph, some countries such as the UK and Belgium get lower average scores while they are often perceived as countries with sophisticated systems protecting workers. There are many possible reasons for this observation.

Firstly, the absence of clauses relevant to overtime or annual leave does not always imply low worker friendliness. There may already be clear laws and regulations in specific countries regarding these aspects, hence the abscence of need for CBAs to have sections dedicated to them, which explains why the assumption that absence means worker unfriendliness is not always correct. But it is important to realize that the score indicates the worker friendliness of CBAs themselves without considering the contexts.

Secondly, the availability of CBAs in the dataset varies across countries. It can be difficult to collect CBAs from countries such as the UK due to reasons like privacy concerns, and the small and biased sample may also affect the accuracy of the final score.

Thirdly, there are also limitations regarding binary indicators. In the current scoring system, the indicators mostly concern the existence of certain clauses, but the existence of clauses does not have anything to do with the quality of these clauses and does not necessarily mean that those clauses are enough to protect labor’s rights.

This indicator is based on three different measures, namely concretness, readability and lexical density, which were used to observe how easy it is for the workers to understand CBAs. Concreteness refers to the amount of abstract versus concrete words used in a text. Texts with relatively more concrete words are more accessible than texts with relatively more abstract words. While this measures the use of referentiality to concrete objects, the second aspect which referred to readability measures the years of education one would need to be able to understand a piece of text. This is usually evaluated through the amount of long words and long sentences. Finally, lexical density looks at language from a semantic perspective and is a measure of the number of different words that are used. The hypothesis is that for a text to be considered readable, it should require fewer years of education and should have low lexical density. The figure below shows the text accessibility scores for various languages, and it can be seen that Slovak’s CBAs are considerably more reader-friendly than Indonesian CBAs.

In summary, the project identified a number of ways that the ‘worker-friendliness’ of agreements might be measured, making use of text mining methods to analyse and score agreements on various indicators. By using and visualising these scores, the team has been able to find new methods of evaluating agreements at a glance, in ways that might facilitate understanding of these agreements for labour market researchers and workers in general. However, a number of challenges and limitations have been identified that invite further research into the secrets of collective bargaining agreements.

• For a detailed description of the methodology used and further discussion, see the final output report.
• Do not forget to test drive the tool on its current website.
• To read the outputs of other groups, check the #DHH21 site.