View source for State-hired caregiver

<!-- proposed WesisPedia url (by a04_m2w):
https://seth.informatik.uni-bremen.de/wesis/wiki/index.php/State-hired caregiver
-->

{{Indicator
|datatype = Numeric
|scale = Multinomial
|valuelabels = <ul><li>0 = “No” </li><li>1 = “Yes” </li><li>-888 = “Absence of long-term care system” </li><li>-999 = “No information available” </li></ul>
|techname = health_ltc_gen_tob_hired_cg
|category= [[Health and long-term care|Health and long-term care]]
|label = State-hired caregiver
|relatedindicators = NA (no information available)
|description = The indicator shows whether a country legally offers employment as state-hired caregiver for care givers as a long-term care benefit. Countries/years in which such a benefit is available based on legal regulations are coded ‘1’; countries/year in which no such benefit exists are coded ‘0’.

State-hired caregiver status is one type of regulatory benefit offered for persons who provide informal care to family members or other close persons (care givers). The indicator is based on the following definition of state-hired care giver:  Regulatory benefit scheme providing care givers with a state-supported contract to provide care for a family member or otherwise close person.

The indicator is part of the Generosity of Long-Term Care Systems dataset (GLTCS) which measures de jure inclusiveness and scope of benefits of all countries with long-term care systems worldwide (Viero & Fischer, forthcoming). Besides the benefit portrayed in this indicator, the GLTCS contains 16 more different in-kind, cash and regulatory long-term care benefits aimed at care recipients and care givers which are also presented in WeSIS.
|codingrules = Countries/years in which the benefit is available based on legal regulations are coded ‘1’; countries/year in which no such benefit exists are coded ‘0’. Missing values coded in the following way: The code -888 is employed for countries which do not have a long-term care system (see Fischer, Sternkopf & Rothgang, 2023; de Carvalho & Fischer, 2020); these countries were excluded from data collection. The code -999 is employed for cases where information is missing.

Multiple data sources were employed and triangulated for constructing the indicator: national laws and regulations, academic publications and grey literature and websites such as report series from international organisations.

The quality of each data point is rated by two quality ratings, plausibility and reliability assessment. Plausibility concerns are indicated if a) contradicting information was retrieved by stating “Yes, due to contradicting sources”; b) information was limited to single and/or unsound sources and values are thus uncertain stating “Yes, due to limited sources”. The reliability rating is based on two parameters: the type of sources and information triangulation between different sources. There are three levels of reliability as defined below:

* High reliability
** Information is contained in an official law or comparable legislative document in vigour during the analysed time-point. OR
** Information is consistent across at least three different sources, with two of them being either an independent, uncorrelated scientific publication (e.g., academic papers and chapters in books) and/or official government-related sources (e.g., ministry websites, government reports and bulletins).
*Medium reliability
** Information is consistent across at least three different sources, none of which is either a law, a scientific publication, or an official government-related source. OR
** Information is consistent across less than three different sources, with at least one of them being a scientific publication or an official government-related source.
* Low reliability
** Information is consistent across less than three different sources, none of which is either a law, a scientific publication, or an official government-related source. 

Definitions, data collection procedures and sources are outlined in detail in Viero & Fischer (forthcoming).
|citation = <ul><li>Viero, Davide; Fischer, Johanna (forthcoming), The Generosity of Long-Term Care Systems dataset (GLTCS). SFB 1342.</li></ul>
|relatedpublications = <ul><li>Fischer, J., Sternkopf, M., & Rothgang, H. (2023). Covering a new social risk: The introduction of long-term care systems worldwide. In I. Mossig & H. Obinger (Eds.), SOCIUM SFB Working Papers: Vol. 25. Mapping Global Dynamics of Social Policy (pp. 32–35). Bremen: Collaborative Research Centre 1342.  https://doi.org/10.26092/elib/2559 </li><li>De Carvalho, G., & Fischer, J. (2020). Health and long-term care system introduction and reform – concepts and operationalisations for global and historical comparative research. SFB 1342 Technical Paper Series, 3. https://doi.org/10.26092/ELIB/539 </li></ul>
|projectmanagers = Davide Viero and Johanna Fischer (on behalf of the A07 project)
|datarelease = <ul><li> Version 0.001: Initial release.</li></ul>
|revisions = No revisions yet
|sources = <ul><li> For a detailed overview of all sources per country used please see: Viero, Davide; Fischer, Johanna (forthcoming), The Generosity of Long-Term Care Systems dataset (GLTCS). SFB 1342.</li></ul>
}}