Equalising function

Quick info
Data type	Numeric
Scale	Metric
Value labels	not applicable
Technical name	labor_equa_func
Category	Labour and labour market
Label	Equalising function
Related indicators	SPE-Type of employment law (string) SPE-Type of employment law Type of employment law (string) Standard-setting function Privileging function

"Equalising function" measures the level of protection of social groups of employees who are discriminated against, as part of a cultural phenomenon or related to non-standard employment contracts in individual labour law. It refers refers to a form of legal segmentation which arises from contractual freedom, which allows employers to circumvent employment protection resulting in inequalities between groups. The function is measured by 15 indicators and includes norms relating to the two dimensions discrimination and flexibilisation and focuses on two aspects each (access, working conditions, restriction, equal treatment). The index ranges from 0 to 1 where 1 is the maximum value reflecting the highest possible level of norm-related equalising.
The variable is available for 115 countries from 1970 to 2013, using 8 World of Labour (WoL) variables and 7 CBR-LRI variables (see Dingeldey et al. 2020, 2022). The data from CBR Labour Regulation Index Dataset was coded using provisions of law and relevant court decisions, which are taken from secondary sources, national law databases, and ILO NATLEX data (see Adams et al. 2017, 2023). The 8 World of Labour (WoL) variables were coded using statutory law, only. The different coding basis (text for the coding of legal norms) leads to a different mapping of the scope of law between the CBR and WoL variables. The "Equalising function" is recreated from the SPE-typology (see Dingeldey et al. 2020), which distinguishes the standard-setting (S), privileged (P) and compensatory (E) functions of labor law.

Coding rules

The index calculation is based on 7 CBR-LRI and 8 WoL indicators; the first 8 variables are classified as 'discrimination', and the remaining 7 as 'flexibilisation':

• The law provides for equal opportunities for men and women in terms of access to employment: WoL, V1
• The law provides for regulation of positive discrimination in order to overcome labour discrimination of women: WoL, V1
• The law provides for equal opportunities concerning ethnicity/race in terms of access to employment: WoL, V1
• The law provides for regulation of positive discrimination in order to overcome labour discrimination of groups disadvantaged in terms of ethnic/racial backgrounds: WoL, V1
• Equal pay for work of equal value is legally provided for: WoL, V1
• The law provides for equal opportunities for men and women in terms of working conditions: WoL, V1
• The law provides for equal opportunities in terms of working conditions concerning ethnicity/race: WoL, V1
• Employees enjoy the right to a universal minimum wage: WoL, V1
• Fixed-term contracts are allowed only for work of limited duration: CBR-LRI, A.4
• Maximum duration of fixed-term contracts: CBR-LRI, A.6
• Agency work is prohibited or strictly controlled: CBR-LRI, A.7
• Part-time workers have the right to equal treatment with full-time workers: CBR-LRI, A.2
• The cost of dismissing part-time workers is equal in proportionate terms to the cost of dismissing full-time workers: CBR-LRI, A.3
• Fixed-term workers have the right to equal treatment with permanent workers: CBR-LRI, A.5
• Agency workers have the right to equal treatment with permanent workers of the user undertaking: CBR-LRI, A.8

Assessment of the scale level in Dingeldey et al. (2022) and Adams et al. (2017, 2023) and the description of the values in the template differ. As Adams et al. (2023) state “Some indicators use binary coding but most use non-binary or graduated scores. The template indicates the approach to scoring in each case. Some indicators are expressed as cardinal variables (for example, those relating to minimum qualifying periods of continuous employment) but most are expressed on an ordinal scale.” (p. 7) and Dingeldey et al. (2022) state “The nature of each indicator’s scale depended on the number of possible states that we could envisage for that variable; in the end, all indicators that we developed had either binary (true and false) or graduated scales, some of which, drawing on the CBR, were ordinal in nature, and some cardinal (in the case, for example, of certain working time standards).” (p. 582).
Using the 15 variables, an additive index was calculated by adding the values of all variables in the aspects within the dimensions 'discrimination' (N=8) and 'flexibilisation' (N=7) and dividing by their number. Each dimension is assigned identical weights, as are all variables of the same dimension. Finally, the two dimensions are added together and divided by two to generate the index "Equalising function". The calculations reproduce the SPE typology from Dingeldey et al. 2020, 2022 with the exact same data (in consultation with the persons responsible for the calculations and exchange of the STATA-do files). All missing values were excluded from the analysis.

Bibliographic info

Citation: Schäfer, Andrea, Marina Carlino, Irene Dingeldey, Heiner Fechner, Ulrich Mückenberger and (2024). Equalising function data (2024). University of Bremen.

Related publications:

• Adams, Zoe, Bhumika Billa, Louise Bishop, Simon Deakin and Tvisha Shroff (2023). CBR Labour Regulation Index (Dataset of 117 Countries, 1970-2022) - Codes and Sources. Centre for Business Research, University of Cambridge. at: https://doi.org/10.17863/CAM.9130.2
• Carlino, Marina, Fechner, Heiner, and Schäfer, Andrea (2025, forthcoming). Using leximetrics for coding legal segmentation in employment law: The development and potential of the Worlds of Labour database. In I. Dingeldey, H. Fechner, & U. Mückenberger (Eds.), Constructing Worlds of Labour. Coverage and Generosity of Labour Law as Outcomes of Regulatory Social Policy. Palgrave Macmillan. p.53-83
• Deakin, Simon, Johna Armour and Mathias Siems (2023). CBR Leximetric Datasets [Updated 2023]. Apollo - University of Cambridge Repository. https://doi.org/10.17863/CAM.9130.2
• Dingeldey, Irene, Heiner Fechner, Jean-Yves Gerlitz, Jenny Hahs, and Ulrich Mückenberger (2020). Measuring Legal Segmentation in Labour Law. SOCIUM SFB 1342 Working Papers No. 5, Bremen: SOCIUM, University of Bremen. https://www.socialpolicydynamics.de/f/90e3891ffd.pdf
• Dingeldey, Irene, Heiner Fechner, Jean-Yves Gerlitz, Jenny Hahs, and Ulrich Mückenberger (2022). Worlds of Labour: Introducing the Standard-Setting, Privileging and Equalising Typology as a Measure of Legal Segmentation in Labour Law, Industrial Law Journal, 51(3), p.560–597

Misc

Project manager(s): Responsible for data editing, calculation, description (WESIS) and entry: Andrea Schäfer (2021-2025); Responsible for data coding: Heiner Fechner (2018-2025), Marina Carlino (2022-2025); Principal Investigator: Irene Dingeldey, Ulrich Mückenberger; Student assistants for coding (alphabetical ordering): Julia Bode, Jessica Bonn, Daniel Euler, Jan-Christopher Floren, Maxime Fischer, Jennifer Götte, Eliko Hagen, Désirée Hoppe, Irina Kyburz, Alexandra Kojnow, Tarek Mahmalat, Karolin Meyer, Oguz Mermut, Johanna Nold, Tanusha Pali, Johannes Ramsauer, Max Sudhoff, Kristina Walter, Caroline Zambiasi

Data release:

• Version 0.001: Initial release with data from CBR-LRI published in April 2017 (data for the period from (in most cases) 1970 to 2013) + 8 variables from WoL, V1

Revisions: No revisions yet

Sources

• Deakin, Simon, Johna Armour and Mathias Siems (2017). CBR Leximetric Datasets [updated]. [Dataset]. Apollo - University of Cambridge Repository. https://doi.org/10.17863/CAM.9130
• The sources used for coding the WoL-values are not available (for more information on sources pls contact the person responsible for data coding – see entry: Project manager(s)) -.