Fault fictions: systematic biases in the conceptualization of fault-zone architecture

Fault fictions: systematic biases in the conceptualization of fault-zone architecture
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DOI:
10.1144/sp496-2018-161
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发表时间:
2020-01-01
期刊:
INTEGRATED FAULT SEAL ANALYSIS
影响因子:
--
通讯作者:
Caine, J. S.
Caine, J. S.
中科院分区:
其他
文献类型:
--
作者:
Shipton, Z. K.;Roberts, J. J.;Caine, J. S.

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心理模型是人类对现实世界的内在表征,在我们理解和推理不确定性、探索潜在选择和做出决定方面发挥着重要作用。心理模型在地球科学中还没有受到太多的关注,然而系统偏差可以影响任何地质调查:从如何构思问题,通过选择适当的假设和数据收集/处理方法,到结果的概念化和交流。我们利用认知科学和系统动力学的发现,结合野外地质学的知识和经验,来考虑地球科学中心理模型所呈现的局限性和偏见,特别是它们对断层物理性质预测的影响。我们强调了特定于地质调查的偏见,并提出了消除偏见的策略。这样做将增强多个数据源的整合能力,并将可控的地质不确定性降至最低,从而开发出更稳健的地质模型。至关重要的是,需要标准化的程序来防止偏见,允许将来自多个研究的数据结合起来,并进行假设的交流。虽然我们使用断层来说明心理模型中的潜在偏差以及这些偏差的含义,但我们的发现可以应用于整个地球科学。
Mental models are a human's internal representation of the real world and have an important role in the way we understand and reason about uncertainties, explore potential options and make decisions. Mental models have not yet received much attention in geosciences, yet systematic biases can affect any geological investigation: from how the problem is conceived, through selection of appropriate hypotheses and data collection/processing methods, to the conceptualization and communication of results. We draw on findings from cognitive science and system dynamics, with knowledge and experiences of field geology, to consider the limitations and biases presented by mental models in geoscience, and their effect on predictions of the physical properties of faults in particular. We highlight biases specific to geological investigations and propose strategies for debiasing. Doing so will enhance how multiple data sources can be brought together, and minimize controllable geological uncertainty to develop more robust geological models. Critically, there is a need for standardized procedures that guard against biases, permitting data from multiple studies to be combined and communication of assumptions to be made. While we use faults to illustrate potential biases in mental models and the implications of these biases, our findings can be applied across the geosciences.