View source for The cost of dismissing part-time workers is equal in proportionate terms to the cost of dismissing full-time workers (WoL, V2)

{{IndicatorForm
|datatype=Numeric
|scale=Metric
|scale=Metric
|scale=Metric
|valuelabels=not applicable
|techname=labor_equity_part_dismiss
|category=Labour and labour market
|label=Dismissing costs for part-time workers is proportional
|relatedindicators=<ul>
<li>[[Fixed-term contracts are allowed only for limited duration]]</li>
<li>[[Maximum duration of fixed-term contracts]]</li>
<li>[[Agency work is prohibited or strictly controlled]]</li>
<li>[[Part-time workers have the right to equal treatment]]</li>
<li>[[Fixed-term workers have the right to equal treatment]]</li>
<li>[[Agency workers have the right to equal treatment]]</li>
</ul>
|description=This variable measures whether and to what extent part-time employees have the same protection against dismissal as full-time employees.<br>
Unequal treatment can affect general terms and conditions of employment; with regard to protection against dismissal, there are many special disadvantages, particularly for marginal part-time jobs and zero-hour jobs. In particular, there are disadvantages in terms of notice periods, severance payment and protection against unfair dismissal. The variable measures whether and to what extent the law regulates equality in terms of employment conditions for part-time workers in respect to full-time workers.<br>
This variable is derived and minimally modified from the CBR Labour Regulation Index Dataset (‘CBR-LRI’), which provides data on employment law across 117 countries spanning the years from (in most instances) 1970 to 2022, with the exception of post-socialist countries (refer to Adams et al. 2017, 2023).  The current CBR-LRI data points were reviewed, and any discrepancies in values were adjusted in accordance with the WoL coding rules. Additionally, data points from before 1970 or equivalent timeframes for former Soviet bloc countries were included (cf. Fechner/Carlino 2025).  In addition to the 115 countries with populations exceeding 500,000 as classified by CBR-LRI, 37 more countries have been included (cf. Fechner/Carlino 2025).  Core differences concerning the original CBR-LRI data:
<li>The CBR Labour Regulation Index Dataset was developed by analysing legal provisions, collective agreements  (if generally binding or containing national standards) and pertinent court rulings, sourced from secondary materials, national legal databases, and ILO NATLEX data (cf. Adams et al. 2017, 2023).  WoL exclusively codes statutory law, resulting in modifications to outcomes that include collective agreements and court decisions that define entitlements.</li>
|codingrules="Equals 1 if as a matter of statutory law part-time workers enjoy proportionate rights to full-time workers in respect of dismissal protection (notice periods, severance pay and unjust dismissal protection).
Equals 0 otherwise.
Scope for further gradation 0 and 1 to reflect changes in the strength of the statutory law."<br>
For detailed coding rules, please consult [https://doi.org/10.26092/elib/4191 Fechner/Carlino 2025].
|citation=Fechner, Heiner and Marina Carlino (2025). Worlds of Labour (WoL) Leximetric Dataset. University of Bremen.
|relatedpublications=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 <br>
Carlino, Marina, Fechner, Heiner, and Schäfer, Andrea (2025). 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. pp.53-83<br>
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, Ulrich Mückenberger, Worlds of Labour: Introducing the Standard-Setting, Privileging and Equalising Typology as a Measure of Legal Segmentation in Labour Law, Industrial Law Journal, Volume 51, Issue 3, September 2022, Pages 560–597, https://doi.org/10.1093/indlaw/dwab016<br>
Fechner, Heiner, and Marina Carlino (2025). Coding Legal Segmentation in Employment Law. The Worlds of Labour (WoL) Dataset. SFB 1342 Technical Paper Series, 22. Bremen: SFB 1342. https://doi.org/10.26092/elib/4191
|projectmanagers=Responsible for data coding: Heiner Fechner (2018-2025), Marina Carlino (2022-2025).<br>
Responsible for data editing, description (WESIS) and entry: Heiner Fechner (2025), Andrea Schäfer (2021-2025), Jenny Hahs (2018-21), Jean-Yves Gerlitz (2018-20).<br>
Principal Investigators: Irene Dingeldey, Ulrich Mückenberger.<br>
Student assistants (alphabetical ordering): Max Anders, 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, Gerrit Pantel, Johannes Ramsauer, Max Sudhoff, Kristina Walter, Caroline Zambiasi.
|datarelease=Version 0.001: Initial release December 2025.
|revisions=No revisions yet.<br>
This is the first version of the dataset of the thoroughly revised Version 2 WoL template; for the first time, all variables including those originally stemming from CBR-LRI have been coded/revised under WoL criteria. A preliminary version with compiled data (CBR-LRI and WoL) has been published in WeSIS marked by "CBR-LRI-based" and "WoL, V1".
|sources=Own coding, partially based on coding by CBR-LRI.<br>
Fechner, Heiner, and Marina Carlino (2025). Coding Legal Segmentation in Employment Law. The Worlds of Labour (WoL) Dataset. SFB 1342 Technical Paper Series, 22. Bremen: SFB 1342. https://doi.org/10.26092/elib/4191<br>
Partially identical (after revision by WoL) with the original CBR-LRI coding, to be found in: <br>
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
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