University of Eastern Finland, Department of Social Science, P.O. Box 1627, FI 70211 Kuopio, Finland.
Fudan University, Department of Social Development and Public Policy, No. 220 Handan Road, 200433 Shanghai, China.
Child Abuse Negl. 2024 Sep;155:106963. doi: 10.1016/j.chiabu.2024.106963. Epub 2024 Aug 5.
Child protection notifications aim to secure the wellbeing of children. However, there is a large variation in the implementation of notifications across the municipalities in Finland.
This article explores whether the threshold of child protection notifications is higher in municipalities with a high level of socio-economic risk factors, as assumed by the inverse intervention law.
The study is based on the system-level data of Finnish municipalities, and their socio-economic indicators for the period of 2010-2021.
A cluster analysis is used to group Finnish municipalities, based on the level of socio-economic risk factors, and a panel regression analysis, to verify whether these factors act as risk factors or as driving forces of inverse intervention law.
The municipalities with a high level of risk factors have the higher threshold level for child protection notifications compared to other municipalities. In all municipalities, the share of single-parent families acts as a risk factor, while the share of residents with higher education acts as a driver of the inverse intervention law. Reduction of unemployment and income inequalities are also recognised as drivers of this law, but only in municipalities with a relatively higher level of risk factors.
This study promotes the inverse intervention law, and contribute to the understanding of the driving forces of this law. Further, there is a difference in the threshold level of child protection notifications among municipalities which is based on their socio-economic context. Children are in an unequal position in relation to the municipality in which they live.
儿童保护通知旨在保障儿童的福祉。然而，芬兰各城市在实施通知方面存在很大差异。
本文旨在探讨儿童保护通知的门槛是否在社会经济风险因素较高的城市更高，这是反向干预法所假设的。
本研究基于芬兰各城市的系统级数据及其 2010-2021 年期间的社会经济指标。
使用聚类分析根据社会经济风险因素的水平对芬兰城市进行分组，并进行面板回归分析，以验证这些因素是作为风险因素还是作为反向干预法的驱动力。
高风险因素的城市的儿童保护通知门槛比其他城市更高。在所有城市中，单亲家庭的比例都是风险因素，而受过高等教育的居民比例则是反向干预法的驱动力。减少失业和收入不平等也被认为是该法律的驱动力，但仅在风险因素相对较高的城市。
本研究促进了反向干预法，并有助于理解该法律的驱动力。此外，各城市之间儿童保护通知门槛存在差异，这取决于其社会经济背景。儿童在与其居住的城市相关的方面处于不平等地位。
