causality
简明释义
n. <正式>因果关系，因果性；诱发性
复 数 c a u s a l i t i e s
英英释义
Causality refers to the relationship between cause and effect, where one event (the cause) leads to the occurrence of another event (the effect). | 因果关系是指原因与结果之间的关系，其中一个事件（原因）导致另一个事件（结果）的发生。 |
单词用法
因果关系 | |
因果推断 | |
建立因果关系 | |
因果原则 | |
因果效应 | |
因果分析 |
同义词
反义词
| 随机性 | The experiment yielded results that were largely due to randomness. | 实验得出的结果主要是由于随机性。 | |
| 混乱 | In a chaotic system, predicting outcomes becomes nearly impossible. | 在一个混乱的系统中，预测结果几乎是不可能的。 |
例句
1.Computers are not good at dealing with causality.
电脑并不擅长处理因果关系。
2.Vertical causality occurs when the event publisher resides on a different layer than the event receiver.
当事件发布者与事件接收者位于不同层时，发生垂直因果关系。
3.I call this lateral or horizontal causality.
我把这称为横向因果关系。
4.Of course, it's not clear which way the causality runs—whether profitable companies feel rich enough to splash out on CSR, or CSR brings profits.
当然，因果不很清楚。究竟是公司很有钱才把精力花费在社会职责上，还是公司的社会职责表现为公司带来的巨额的利润。
5.Second, I don't think there is a sufficiently rigorous approach to causality.
第二点，我不认为这里有足够严密的因果性。
6.Computer scientist Danny Hillis has noted that computation, particularly networked computation, exhibits a nonlinear causality field. He wrote.
计算机科学家丹尼·希利斯(8)指出，计算，特别是网络计算，呈现了一个非线性的因果关系域。
7.Some basic philosophical teaching would be rather useful to enable economists to think about causality with more of an open mind.
一些基本的哲学教学对于这些经济学派是有极大用途的，能够让他们更为开阔的思考事物的因果关系。
8.B has to be caused by something and a happened first, so they assign causality.
如果B真的因为某些事情而发生了，而A又在之前发生，所以他们刻意安排这种因果关系。
9.Horizontal causality occurs when the event publisher resides on the same layer in an architecture's virtual layers as the event receiver.
当事件发布者与事件接收者位于架构虚拟层中的同一层时，发生水平因果关系。
10.In philosophy, debates about causality 因果关系 often focus on whether it is a fundamental aspect of reality.
在哲学中，关于因果关系的辩论通常集中在它是否是现实的基本方面。
11.The documentary explored the causality 因果关系 of climate change on natural disasters.
这部纪录片探讨了气候变化对自然灾害的因果关系。
12.Understanding causality 因果关系 is crucial in developing effective public health policies.
理解因果关系对制定有效的公共卫生政策至关重要。
13.The researchers conducted an experiment to determine the causality 因果关系 between sleep deprivation and cognitive performance.
研究人员进行了一项实验，以确定睡眠剥夺与认知表现之间的因果关系。
14.Establishing causality 因果关系 in social sciences can be challenging due to numerous confounding variables.
在社会科学中，建立因果关系可能会因为众多混杂变量而变得困难。
作文
Causality is a fundamental concept that underpins much of our understanding of the world around us. It refers to the relationship between causes and effects, where one event (the cause) leads to the occurrence of another event (the effect). Understanding causality (因果关系) is essential in various fields, including science, philosophy, and everyday life. In science, for instance, researchers strive to establish causal relationships through experiments and observations. When a scientist conducts an experiment, they often manipulate one variable to see how it affects another. This process helps them determine whether a specific factor is responsible for a certain outcome.In philosophy, causality (因果关系) has been a topic of debate for centuries. Philosophers like David Hume questioned the nature of causation, arguing that we cannot directly observe causal connections; instead, we infer them based on patterns and regularities we observe in the world. This raises important questions about the limits of human understanding and the reliability of our judgments regarding cause and effect. Can we truly know that one event causes another, or are we merely observing correlations?In everyday life, we constantly make decisions based on our understanding of causality (因果关系). For example, when we notice that it rains after dark clouds appear, we begin to associate the two events. This understanding influences our behavior; we might carry an umbrella when we see dark clouds because we believe that the clouds (cause) will lead to rain (effect). However, this simplistic view can sometimes lead us astray. Correlation does not always imply causation, and misinterpreting relationships can result in poor decision-making.Consider the classic example of smoking and lung cancer. Numerous studies have established a strong correlation between smoking and the incidence of lung cancer. However, establishing causality (因果关系) requires more than just observing this correlation. Researchers must consider other factors, such as genetics, environmental influences, and lifestyle choices. Through rigorous scientific methods, they conclude that smoking is a significant causal factor in the development of lung cancer, but it is essential to acknowledge that not every smoker will develop the disease.The importance of understanding causality (因果关系) extends beyond academic discussions; it has practical implications in policy-making and public health. For example, if a government wants to reduce smoking rates to improve public health, it must understand the causal factors that lead individuals to smoke. By addressing these root causes, such as stress, social influences, and lack of education, policymakers can create more effective interventions.Furthermore, in the realm of technology and data analysis, understanding causality (因果关系) is crucial for making informed decisions. With the rise of big data, businesses often analyze vast amounts of information to identify trends and patterns. However, without a clear understanding of causal relationships, companies risk making decisions based on misleading correlations. For instance, a company might notice that sales increase during a particular season and assume that their advertising campaign is the cause. Yet, without further investigation, they may overlook other factors, such as seasonal demand or economic conditions, that could also be influencing sales.In conclusion, causality (因果关系) is a vital concept that shapes our understanding of the world. Whether in scientific research, philosophical inquiry, or everyday decision-making, recognizing the relationship between causes and effects is essential. By critically examining the factors that contribute to outcomes, we can make better-informed choices and foster a deeper understanding of the complexities of life.
