Foresight and Understanding: An Enquiry into the Aims of Science.

One of the major aims of science, it is commonly held, is to provide explanations. Philosophers of science have tried to understand what it is to provide a scientific explanation, what distinguishes good from bad explanations, and why explanations are valuable. This chapter goes through the main answers that have been elaborated in the last decades. It starts with a detailed discussion of the famous deductive-nomological (DN) model of explanation proposed by Hempel and Oppenheim. Then, the two main rivals to the DN model, the causal theory and the unificationist theory, are introduced and discussed. Some other contemporary approaches are sketched out in the closing section.

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Uncertainty in Scientific Explanations

Uncertainty ◽

10.1093/oso/9780190871666.003.0012 ◽

2019 ◽

pp. 166-178

Author(s):

Kostas Kampourakis ◽

Kevin McCain

Keyword(s):

Natural Phenomena ◽

Scientific Explanations ◽

Aims Of Science

One of the chief aims of science is understanding. The primary way that we achieve understanding of natural phenomena is by constructing explanations of how and why the phenomena occur as they do. The explanations provided by science are inherently uncertain. Due to the complexity of the phenomena being explained and our limitations as humans, scientists rely on models when constructing explanations. By their vary nature, models are uncertain because they essentially involve idealizations (abstractions or distortions of the facts) for the purpose of simplification. Although scientists legitimately infer that the best explanation of a given phenomenon is true, this method of inference is always uncertain for at least two reasons. The first is simply that the data being explained are limited (i.e., there is always more data that could have been gathered). The second is that there are always alternative explanations that might later be discovered.

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EDITORIAL

American Journal of Islam and Society ◽

10.35632/ajis.v8i1.2640 ◽

1991 ◽

Vol 8 (1) ◽

pp. v-vii

Author(s):

Sayyid M. Syeed

Keyword(s):

Traditional Culture ◽

Indiana University ◽

Basic Principles ◽

Near Eastern ◽

Aims Of Science ◽

The People ◽

Massive Scale ◽

Muslim Intellectuals ◽

Islamic Civilization

We report with great sadness the death of Victor Danner, a friend ofIslam and Muslims, a graduate of Georgetown and Harvard, and Chairmanof the Department of Near Eastern Languages and Cultures at Indiana University,BloomingtOn, Indiana. Darner's latest publication was The Islamic Traditiontion: An Introduction. W have been inviting Muslim anti non-Mush scholarsfrom time to time to present their responses to the International Instituteof Islamic Thought’s caIl for the Islamization of Knowledge. So far, we havebeen very lucky to have had the opportunity to listen to the late Fazlur Rahman,Sayyed H. Nasr, Abdulaziz Sachedina and others who joined this debateat the IIIT headquarters. Some of these responses have been published invarious issues of AJISS.Victor Danner treated us to his response on May 15, 1989, when hepresented his paper, which appears in this issue under the title of “WesternEvolutionism in the Muslim World,” at the IIIT headquarters. In this article,he launches an eloquent plea for the rediscovery and reexploration of thevarious schools of thought in Islam and their subsequent adaptation to theneeds and circumstances faced by contemporary Muslims. He reminds usthat past attempts at reform by Muslim intellectuals were based on a readaptationof the traditional techniques of Islam which, when presented in a freshmanner as a solution to the needs faced by their own contemporaries, gavethe doctrine of tawhid “a powerful radiance that had a convincing allure toit.” This is followed by an examination of the origins of evolutionary thinkingin the West, how its eventual acceptance and spread throughout the Westultimately displaced Christian beliefs and institutions on a massive scale,and how the resulting secular civiIization produced by it is threatening tosweep aside and destroy traditional Islamic civilization. In closing, he stateshis hope that a better understanding of this phenomenon among the Muslimintelligentsia and the people at large will cause them to wake up to this dangerand begin to work for the preservation of the ”traditional culture of Islam.”Our first article in this issue is by Imaduddin Khalil, and addresses theQur’an’s relationship vis-his modem science. After ruling out the Qur’anas a book or textbook of scientific knowledge, he proceeds to discuss thephilosophy and aims of science and the basic principles of Islam. He beginswith the role of humanity on earth as the khaEfuh of Allah, moves on tothe principles of tawazun (balance) and taskhir (an Islamic concept statingthat the world and nature have been made subservient to humanity), andcloses with the principle of a link between creation and the Creator. Khalilviews the Qur’anic methodology as being a “methodology of discovery” of ...

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Asking Too Much, Receiving Too Little: Indigenous Identity and the Aims of Science

TOPIA Canadian Journal of Cultural Studies ◽

10.3138/topia.22.5 ◽

2010 ◽

Vol 22 ◽

pp. 5-34

Author(s):

Adam Muller

Keyword(s):

Indigenous Identity ◽

Aims Of Science

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Future Aims of Science Curriculum for Primary School

Cultura ◽

10.5840/cultura20074212 ◽

2007 ◽

Vol 4 (2) ◽

pp. 176-183

Author(s):

Kiymet Selvi ◽

Keyword(s):

Primary School ◽

Science Curriculum ◽

Aims Of Science

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Science on Demand

Epistemology & Philosophy of Science ◽

10.5840/eps202057456 ◽

2020 ◽

Vol 57 (4) ◽

pp. 52-61

Author(s):

Stephen Turner ◽

Keyword(s):

Public Good ◽

Nature Of Science ◽

Basic Science ◽

Competitive System ◽

On Demand ◽

Funding System ◽

Aims Of Science ◽

Funding Agencies ◽

Peer Approval ◽

Reliable Knowledge

Characterizing science as a public good, as Steve Fuller notes, is a part of an ideological construal of science, linked to a particular portrayal of science in the postwar era that was designed to provide a rationale for the funding of pure or basic science. The image of science depended on the idea of scientists as autonomous truth-seekers. But the funding system, and other hierarchies, effectively eliminated this autonomy, and bound scientists tightly to a competitive system in which the opportunity to pursue ideas in science depended on peer approval in advance. Funding agencies then turned to assessments of impact. John Ziman had already recognized the effects of these changes in the nature of science, and characterized it as “reliable knowledge” produced on demand from funders. As the competition for funds increased, there were further changes in the nature of science itself toward “reliable enough” knowledge. This made science into a “good”. but a good in the sense of results produced for funders, a transformation that left the original epistemic aims of science behind.

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Estimating Causal Effects from Nonparanormal Observational Data

The International Journal of Biostatistics ◽

10.1515/ijb-2018-0030 ◽

2018 ◽

Vol 14 (2) ◽

Author(s):

Seyed Mahdi Mahmoudi ◽

Ernst C. Wit

Keyword(s):

Directed Acyclic Graph ◽

Large Scale ◽

Causal Effect ◽

Causal Effects ◽

Data Sampling ◽

Aims Of Science ◽

Daunting Task ◽

Large Systems ◽

Equivalent Systems ◽

Non Gaussian

AbstractOne of the basic aims of science is to unravel the chain of cause and effect of particular systems. Especially for large systems, this can be a daunting task. Detailed interventional and randomized data sampling approaches can be used to resolve the causality question, but for many systems, such interventions are impossible or too costly to obtain. Recently, Maathuis et al. (2010), following ideas from Spirtes et al. (2000), introduced a framework to estimate causal effects in large scale Gaussian systems. By describing the causal network as a directed acyclic graph it is a possible to estimate a class of Markov equivalent systems that describe the underlying causal interactions consistently, even for non-Gaussian systems. In these systems, causal effects stop being linear and cannot be described any more by a single coefficient. In this paper, we derive the general functional form of a causal effect in a large subclass of non-Gaussian distributions, called the non-paranormal. We also derive a convenient approximation, which can be used effectively in estimation. We show that the estimate is consistent under certain conditions and we apply the method to an observational gene expression dataset of the Arabidopsis thaliana circadian clock system.

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