Difference between revisions of "Reinstatement normal remedy for unfair dismissal"
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Revision as of 17:15, 12 March 2020
Quick info | |
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Data type | Numeric |
Scale | Metric |
Value labels |
quasi-metric scale; further gradations between 0 and 1 reflect changes in the strength of the law |
Technical name | labor_reinstate |
Category | Labour and labour market |
Label | Reinstatement normal remedy for unfair dismissal |
Related indicators |
This CBR-LRI indicator measures to what extent reinstatement of an employee is the normal remedy for an unjust dismissal.
Coding rules
The CBR-LRI is a leximetric dataset on employment protection. It quantifies the strength of protection expressed in labour law and functional equivalents such as administrative regulation and collective agreements (see Adams et al. 2017). The scale ranges from "0" to "1" where "0" corresponds to no remedy being available as of right and "1" to reinstatement being the normal remedy for unjust dismissal that is regularly enforced, and gradations between the two values reflect gradtions in the strength of law. For country-specific information see Adams, Bishop and Deakin (2016).
Bibliographic info
Citation:- Adams, Zoe, Parisa Bastani, Louise Bishop, and Simon Deakin. 2017. "The CBR-LRI Dataset: Methods, Properties and Potential of Leximetric Coding of Labour Law." International Journal of Comparative Labour Law and Industrial Relations 33 (1): 59–91. http://kluwerlawonline.com/abstract.php?area=Journals&id=IJCL2017004
- Adams, Zoe, Louise Bishop, and Simon Deakin. 2016. CBR Labour Regulation Index (Dataset of 117 Countries). Cambridge: Centre for Business Research. https://www.repository.cam.ac.uk/bitstream/handle/1810/263766/CBR_LRI_Dataset_Codebook_Methodology_2017_pdf.pdf?sequence=16&isAllowed=y
- Deakin, Simon, Jonas Malmberg, and Prabirjit Sarkar. 2014. "How do labour laws affect unemployment and the labour share of national income? The experience of six OECD countries, 1970-2010". International Labour Review 153 (1): 1-27. https://onlinelibrary.wiley.com/doi/epdf/10.1111/j.1564-913X.2014.00195.x
Misc
Project manager(s):- Irene Dingeldey, Ulrich Mückenberger; research fellows: Heiner Fechner, Jean-Yves Gerlitz, Jenny Hahs
Sources
- Deakin, Simon, John Armour, and Mathias Siems. 2017. "CBR Leximetric Datasets [updated] [Dataset]". https://doi.org/10.17863/CAM.9130