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理解儿童福利数据中土著儿童的过度代表性:德雷克风险与偏差模型的应用

Understanding Overrepresentation of Indigenous Children in Child Welfare Data: An Application of the Drake Risk and Bias Models.

作者信息

Cram Fiona, Gulliver Pauline, Ota Rissa, Wilson Moira

机构信息

Katoa Ltd, Auckland, New Zealand.

New Zealand Family Violence Clearinghouse, School of Population Health, University of Auckland, Auckland, New Zealand

出版信息

Child Maltreat. 2015 Aug;20(3):170-82. doi: 10.1177/1077559515580392. Epub 2015 Apr 22.

DOI:10.1177/1077559515580392
PMID:25908320
Abstract

Child welfare data collected for administrative purposes are often used as a source of information for understanding the population impact of child abuse and neglect (CA/N). This study used administrative data linked at the individual level for a cohort of Aotearoa New Zealand (NZ) children to follow and extend a model developed by Drake et al. In this investigation, we aimed to build an understanding of the high representation of indigenous NZ children in administratively sourced measures of CA/N. Variation in rate ratios (RRs) within infant mortality and birth outcomes considered as possible proxies for actual CA/N RRs leaves open a range of interpretations. Our findings indicate that a more nuanced interpretation of the overrepresentation of indigenous children in administratively recorded maltreatment statistics is required. Rather than considering risk and bias as competing explanations, we suggest an acknowledgment of the impact of colonization and the existence of systemic bias generating increased risk as key drivers. As linked administrative data are increasingly used for research and evaluation, and considered for use in supporting decision making, there is a need for a deeper understanding of the drivers of administratively recorded CA/N in order to effectively address the needs of indigenous populations.

摘要

为行政目的收集的儿童福利数据通常被用作了解虐待和忽视儿童(CA/N)对人口影响的信息来源。本研究使用了与新西兰(NZ)一群儿童在个体层面相关联的行政数据,以跟踪并扩展德雷克等人开发的模型。在这项调查中,我们旨在了解在行政来源的CA/N衡量标准中,新西兰本土儿童为何占比高。在被视为实际CA/N比率可能替代指标的婴儿死亡率和出生结果中,比率比(RRs)存在差异,这留下了一系列解释空间。我们的研究结果表明,对于行政记录的虐待统计中本土儿童占比过高的情况,需要进行更细致入微的解读。我们建议不要将风险和偏差视为相互竞争的解释,而是承认殖民化的影响以及导致风险增加的系统性偏差的存在是关键驱动因素。随着关联行政数据越来越多地用于研究和评估,并被考虑用于支持决策,有必要更深入地了解行政记录的CA/N的驱动因素,以便有效满足本土人口的需求。

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