Difference between revisions of "Privileging function"
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|relatedindicators = | |relatedindicators = | ||
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+ | <li>[[SPE-Type of employment law (string)]]</li> | ||
+ | <li>[[SPE-Type of employment law]]</li> | ||
+ | <li>[[Type of employment law (string)]]</li> | ||
<li>[[Standard-setting function]]</li> | <li>[[Standard-setting function]]</li> | ||
<li>[[Equalising function]]</li> | <li>[[Equalising function]]</li> | ||
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</ul> | </ul> | ||
− | |description = | + | |description = |
− | |codingrules = The index calculation relies on three CBR-LRI and four WoL indicators: | + | "Privileging function" measures the level of norm-related privileging in individual labour law and is a form of legal segmentation. It refers to legal norms that actively promote specific parts of the labour force. These norms link employment protection to specific conditions that are covered by the two dimensions seniority and selectivity and measured by seven indicators. The index ranges from 0 to 1 where 1 is the maximum value reflecting the highest possible level of norm-related privileging. |
+ | The variable is available for 115 countries from 1970 to 2013, using 4 World of Labour (WoL) variables and 3 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 4 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 "Privileging 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.<br> | ||
+ | |codingrules = | ||
+ | The index calculation relies on three CBR-LRI and four WoL indicators, the first 4 variable are subsumed under the dimension 'seniority', the remaining 3 under 'selectivity':<br> | ||
+ | <ul> | ||
+ | <li>The legally mandated notice period for employees increases with seniority: WoL, V1</li> | ||
+ | <li>Legally mandated severance/redundancy payments for employees increase with seniority:WoL, V1</li> | ||
+ | <li>Seniority is a decisive selection criterion in case of redundancy: WoL, V1</li> | ||
+ | <li>Priority in re-employment: CBR-LRI, C.24</li> | ||
+ | <li>General dismissal protection depends on the size of the enterprise: WoL, V1</li> | ||
+ | <li>The law, as opposed to the contracting parties, determines the legal status of the worker: CBR-LRI, A.1</li> | ||
+ | <li>Minimum qualifying period of service for normal case of unjust dismissal: CBR-LRI, C.18</li> | ||
+ | Using these variables, an additive index was calculated by adding the values of all variables in the dimensions "seniority" (N=4) and "selectivity" (N=3) and dividing by their number. Each dimension is assigned identical weights, as are all indications of the same dimension. Finally, the two dimensions are added together and divided by two to generate the index "Privileging 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. | ||
|citation = | |citation = | ||
− | + | Schäfer, Andrea, Marina Carlino, Irene Dingeldey, Heiner Fechner, Ulrich Mückenberger and (2024). Standard-setting function data (2024). University of Bremen. | |
− | |||
− | |||
− | |||
|relatedpublications = | |relatedpublications = | ||
<ul> | <ul> | ||
− | + | <li>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</li> | |
− | Adams, Zoe, Louise Bishop, | + | <li>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 </li> |
− | + | <li>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</li> | |
− | + | <li>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</li> | |
− | + | <li> 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</li> | |
− | |||
− | <li> Deakin, Simon, | ||
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</ul> | </ul> | ||
− | |||
|projectmanagers = | |projectmanagers = | ||
− | + | 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 | |
− | Andrea Schäfer | + | |datarelease = |
− | + | <ul> | |
− | |datarelease = <ul><li>Version 0.001: Initial release</li></ul> | + | <li>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) + 4 variables from WoL, V1</li> |
− | |revisions = No revisions yet | + | </ul>|revisions = No revisions yet |
− | |||
− | |||
|sources = | |sources = | ||
<ul> | <ul> | ||
− | <li> | + | <li>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</li> |
+ | <li>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)) -. </li> | ||
</ul> | </ul> | ||
}} | }} |
Revision as of 12:18, 5 December 2024
Quick info | |
---|---|
Data type | Numeric |
Scale | Metric |
Value labels |
|
Technical name | labor_priv_func |
Category | Labour and labour market |
Label | Privileging function |
Related indicators |
"Privileging function" measures the level of norm-related privileging in individual labour law and is a form of legal segmentation. It refers to legal norms that actively promote specific parts of the labour force. These norms link employment protection to specific conditions that are covered by the two dimensions seniority and selectivity and measured by seven indicators. The index ranges from 0 to 1 where 1 is the maximum value reflecting the highest possible level of norm-related privileging.
The variable is available for 115 countries from 1970 to 2013, using 4 World of Labour (WoL) variables and 3 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 4 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 "Privileging 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 relies on three CBR-LRI and four WoL indicators, the first 4 variable are subsumed under the dimension 'seniority', the remaining 3 under 'selectivity':
- The legally mandated notice period for employees increases with seniority: WoL, V1
- Legally mandated severance/redundancy payments for employees increase with seniority:WoL, V1
- Seniority is a decisive selection criterion in case of redundancy: WoL, V1
- Priority in re-employment: CBR-LRI, C.24
- General dismissal protection depends on the size of the enterprise: WoL, V1
- The law, as opposed to the contracting parties, determines the legal status of the worker: CBR-LRI, A.1
- Minimum qualifying period of service for normal case of unjust dismissal: CBR-LRI, C.18
- 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
- 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) + 4 variables from WoL, V1
- 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)) -.
Using these variables, an additive index was calculated by adding the values of all variables in the dimensions "seniority" (N=4) and "selectivity" (N=3) and dividing by their number. Each dimension is assigned identical weights, as are all indications of the same dimension. Finally, the two dimensions are added together and divided by two to generate the index "Privileging 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). Standard-setting function data (2024). University of Bremen.
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
Revisions: No revisions yet