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Suggested Citation:"Appendix A: Selected Major Social Science Research Methods: Overview." National Research Council. 2012. Using Science as Evidence in Public Policy. Washington, DC: The National Academies Press. doi: 10.17226/13460.

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Appendix A Selected Major Social Science Research Methods: Overview

The social sciences comprise a vast array of research methods, models, measures, concepts, and theories. This appendix provides a brief overview of five common research methods or approaches and their assets and liabilities: experiments, observational studies, evaluation, meta-analyses, and qualitative research. We close with a discussion of new sources of data. We begin with a brief comment on cause and effect.

To inform public policy, researchers often frame their studies in terms of causal conclusions and reason from an intervention to its intended outcomes. Many types of research methods are used for this purpose, as well as statistical analyses.

Research that can reach causal conclusions has to involve well-defined concepts, careful measurement, and data gathered in controlled settings. Only through the accumulation of information gathered in a systematic fashion can one hope to disentangle the aspects of cause and effect that are relevant to a policy setting. Statistical methodology alone is of limited value in the process of inferring causation.

The literature on causality spans philosophy, statistics, and social and other sciences. Our use here is consistent with the recent literature describing causality in terms of counterfactuals, interventions or manipulation, and probabilistic interpretations of causation.

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Suggested Citation:"Appendix A: Selected Major Social Science Research Methods: Overview." National Research Council. 2012. Using Science as Evidence in Public Policy. Washington, DC: The National Academies Press. doi: 10.17226/13460.

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EXPERIMENTS

In the simplest study of an intervention, one group of subjects who receive the intervention (the treatment group) is compared with another group of subjects (the control group) who do not. When the control group receives no other intervention, it serves to depict the counterfactual: what would happen in the absence of the intervention. Many studies, however, are more elaborate and may involve multiple interventions and controls.

An experiment is a study in which the investigator controls the selection of the subjects who may receive the intervention and assigns them to treatment and control groups at random. Experiments can be conducted in highly controlled settings, such as in a laboratory, or in the field, such as at a school, so as to better reflect the context in which an intervention would be implemented in practice. The former assess efficacy, or whether the intervention produces the intended effect. The latter, called randomized controlled field trials (RCFTs), assess effectiveness, or whether the intervention produces the intended effect in practice.

One important advantage of RCFTs is that secondary variables do not confound the effects of an intervention. That is, in an ideal study, an investigator wants to compare the effects of an intervention on a treatment group that is as similar as possible to the control group in all important respects except for having received the intervention. But this ideal can be affected by secondary or intervening variables—other factors by which the treatment group differs from the control group but are not of primary interest—which confound the effects of the intervention. These factors can influence the outcome of an experiment. In an RCFT, however, these secondary variables do not necessarily need to be controlled for in the design or the analysis: randomization obviates even the need to identify the secondary variables.

For many policy purposes, however, the effects of secondary variables are often critical, especially when the intervention is implemented as the result of a policy action. For this reason, the designs of RCFTs are often complex and incorporate individual differences among subjects and contextual variables so that their effects can be analyzed.

Even for the most rigorously conducted RCFTs, however, the results from one setting may not generalize to all other settings. Consequently, it may be difficult to identify “what works” in different settings from just one RCFT. Moreover, the use of RCFTs may be limited because they often require much time and expense in comparison with other approaches, or they may be precluded by ethical considerations.

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Suggested Citation:"Appendix A: Selected Major Social Science Research Methods: Overview." National Research Council. 2012. Using Science as Evidence in Public Policy. Washington, DC: The National Academies Press. doi: 10.17226/13460.

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Still, myriad RCFTs have been successfully conducted to inform social policy. The Digest of Social Experiments (Greenberg and Shroder, 2004) and its successor journal, Randomized Social Experiments, provide many examples.

OBSERVATIONAL STUDIES

Observational studies are nonexperimental research studies in which subjects or outcomes are observed and measured. If two groups are to be compared, the assignment of subjects among the two groups is not under the direct control of the investigator. Two types of observational studies are quasi-experiments (Campbell and Stanley, 1963) and natural experiments (see, e.g., Campbell and Ross, 1968). In the former, the investigator may manipulate the intervention; in the latter, it arises naturally. In neither type of study, however, does the investigator control which subjects receive the treatment. Observational studies can be more than passively observing data and analyzing them: for example, they may involve systematic measurement and aspects of “control,” such as manipulating the timing of an intervention to predefined although nonrandomized groups.

Because they do not involve randomization, however, observational studies may not control for the effects of secondary variables. Without experimental confirmations, the observed outcomes could be the result of any combination of a range of confounding factors. For example, subjects may be self-selected, such as students in a private school who are to be compared with students in a public school, or they may be selected by others but with different characteristics, known or unknown, that may influence the outcome of the intervention. This possible influence is called selection bias. If there is selection bias, how the intervention affects the outcome for the treatment group in comparison with the control group must be described by a model, and that model will always include some assumptions. The model may or may not help with inference for what would have happened in a randomized experiment (see National Research Council, 1998). Moreover, the assumptions underlying the model may not be widely accepted in the scientific community.

Observational studies, however, are important in revealing important associations and in guiding the formulation of theory and models. The observation of a single case can reveal unsuspected patterns and provide explanations for unmotivated forms of behavior. As put by Coburn et al. (2009, p. 1,121): “The in-depth observation made possible by the single case study

Suggested Citation:"Appendix A: Selected Major Social Science Research Methods: Overview." National Research Council. 2012. Using Science as Evidence in Public Policy. Washington, DC: The National Academies Press. doi: 10.17226/13460.

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provides the opportunity to generate new hypotheses or build theory about sets of relationships that would otherwise have remained invisible.”

Observational studies also serve many other important purposes for the use of social science knowledge as evidence for public policy. The country’s wide range of longitudinal studies, for example, provides much information to guide public policy, from the extent to which people save for retirement (information provided by the Health and Retirement Study) to what different types of social welfare program benefits are actually obtained by families living in poverty (information from the Survey of Income and Program Participation). Observational studies, together with historical studies, provide the rich context in which public policy can benefit society. This use may be their most important role.

EVALUATION

Policies are typically implemented with large and highly heterogeneous populations. Even if a policy is based on carefully designed RCFTs or other studies, implementation beyond the confines of the original study population requires careful monitoring and evaluation to make sure that the results observed in the study hold in a larger context.

A researcher must always ask if the new program is producing similar desirable outcomes in the general population as it did in the experimental setting. In the absence of a closely monitored implementation program, issues of measurement, interpretation, and purposeful or accidental deviations from a protocol inevitably creep in, with unpredictable effects on the outcome. When policies are implemented in the general population, it may be done without carefully planned designs and randomized allocation of units to treatments. Unless close monitoring of the policy occurred during implementation, it may not even be known whether the intervention as it was originally devised was what was actually implemented.

Furthermore, the ultimate goal of a policy intervention may well be something to be observed in the future, when follow-up data may be difficult to obtain. For example, although some intermediate outcomes of a program to integrate addicts into the labor force—such as the proportion of participants who are drug free and are employed after a month of treatment—can be measured more or less precisely, it is much more difficult to determine that proportion a year after treatment. Moreover, even if one is able to obtain those data, how could one determine that the results are attributable to the program and not to other factors?

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Suggested Citation:"Appendix A: Selected Major Social Science Research Methods: Overview." National Research Council. 2012. Using Science as Evidence in Public Policy. Washington, DC: The National Academies Press. doi: 10.17226/13460.

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Today’s trend toward accountability means that anyone proposing a new policy or intervention is also expected to prove that the intervention will “work.” Thus, thinking about credible approaches to carry out evaluation studies is almost as critical as conducting the study itself. The principles of experimental design can play an important role, even for observational evaluation.

One approach, for example, is to compare a population before and after an intervention has occurred. As long as the study includes a well-defined reference group and as long as the investigator is reasonably certain that selection bias is not important, such studies can offer some evidence of the effectiveness (or lack thereof) of an intervention. Alternatively, an evaluation study can be planned as an RCFT, in which the goal is to understand whether the original conclusions about the efficacy of the intervention hold when other factors (e.g., the target population) are not exactly the same.

Both experimental and observational studies can be used to evaluate the long-term effects of interventions. An example of such an experimental study is the work of Kellam et al. (2008) on the effect on behavioral, psychiatric, and social outcomes in young adults of a classroom behavior management program carried out when they were in first and second grades. An example of an observational study is the work of Goodman et al. (2012) on the effects of childhood physical and mental problems on adult life, based on an analysis of longitudinal data from the British National Child Development Study.

The evaluation and monitoring of an intervention as implemented is closely related to the more general concept of evolutionary learning, a process to explore how the outcome of interest responds to changes in the original intervention. Consider, for example, a new teaching method shown to be effective in a small class setting. Will it also be as effective when class sizes are large?

A critical aspect of evolutionary learning is the need to proceed in a highly controlled manner in order to understand which factor or which combination of several factors that can be varied are influencing the outcome. Alternatively, a sequence of experiments can be designed in which two or more factors are varied according to a specified plan. In the absence of carefully designed sequential learning studies, it may be difficult to untangle the effect on the outcome of each of several factors under investigation.

As in the case of evaluation and monitoring, there is a theoretical framework developed for sequential learning in studies in which the response of interest is an unknown and may be a complex function of a large

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Suggested Citation:"Appendix A: Selected Major Social Science Research Methods: Overview." National Research Council. 2012. Using Science as Evidence in Public Policy. Washington, DC: The National Academies Press. doi: 10.17226/13460.

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number of inputs. The approach is often known as response surface analysis: it was developed for engineering processes in the early 1950s by Box and Wilson (1951). The idea is to sequentially vary the settings of the input variables so that the response keeps improving.

Although developed for engineering processes, where it is known as evolutionary operation (Box and Draper, 1969), the approach appears to be well suited for the social sciences, in which the relationship between inputs and outputs is typically difficult to measure precisely (see the discussion in Fienberg et al., 1985). It is akin to what is referred to as a learning system that takes full advantage of each application of an intervention and extends the opportunity for discovery throughout the life-cycle of the intervention: its development, implementation, and evaluation.

META-ANALYSIS

Meta-analysis is an application of quantitative methods to combine the results of different studies (see Wachter and Straf, 1990). In such an analysis, a statistical analysis is typically made of a common numerical summary, such as an effect size, drawn from different studies (Hedges and Olkin, 1985). Today, there are many guides to conducting a meta-analysis: see, for example, Cooper (2010) and Cooper et al. (2009). Meta-analyses can lead to new hypotheses and theories and inform the design of an experiment or other research study to test them.

A major purpose of meta-analyses and other research syntheses is to reduce the uncertainty of cause-and-effect assessments of policy or program interventions. By statistically combining the results of multiple experiments, for example, the effect of a policy or program can be estimated more precisely than from any single study of an intervention. Moreover, comparing studies that are conducted with different participants in different settings allows for the examination of how different contexts affect the outcomes of a policy or program. However, if individual studies are flawed, then so will be a meta-analysis of them: thus, meta-analyses often specify standards of quality for the studies to be included.

The amalgamation of results from disparate studies can also be done with careful statistical modeling that is distinct from the approaches of meta-analysis. A good example of this approach is Toxicological Effects of Methylmercury (National Research Council, 2000b): its analysis is based on Bayesian methods developed by Dominici et al. (1999) to pool dose-

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Suggested Citation:"Appendix A: Selected Major Social Science Research Methods: Overview." National Research Council. 2012. Using Science as Evidence in Public Policy. Washington, DC: The National Academies Press. doi: 10.17226/13460.

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response information across a relatively large number of studies. Other examples are in Neuenschwander et al. (2010) and Turner et al. (2009).

Work on understanding how to evaluate effectiveness of a policy intervention from the total body of relevant research assembled from interdisciplinary studies has not been fully developed. An example of success, however, is researchers in early childhood intervention who have integrated knowledge about the developing brain, the human genome, molecular biology, and the interdependence of cognitive, social, and emotional development. These researchers have built a unified science-based framework for guiding priorities for early childhood policies around common concepts from neuroscience and developmental-behavioral research and broadly accepted empirical findings from four decades of program evaluation studies: see, for example, Center on the Developing Child at Harvard University (2007).

QUALITATIVE RESEARCH

In addition to experimental and observational studies, qualitative research can play important roles in developing knowledge about the societal consequences of a policy. The term covers many different types of studies, including ethnographic, historical, and other case studies; focus group interviews; content analysis of documents; interpretive sociology; and comparative and cross-national studies. The research may be derived from documentary sources, field observations, interviews with individuals or groups, and discourse between participants and researchers.

Structured, focused case comparisons are an important example of qualitative research. They are particularly useful when it is difficult to carry out studies that require high levels of control (see George, 1979; George and Bennett, 2005). By compiling and comparing case studies, it is possible to refine theory and also to develop useful assessments of the effectiveness of various types of policy interventions and the conditions that favor the effectiveness of one or another policy strategy. Structured case comparison methods have been used to inform diplomacy (Stern and Druckman, 2000) and assess policy strategies for resolving international conflicts (National Research Council, 2000a), to manage environmental resources at levels from local to global (National Research Council, 2002; Ostrom, 1990), and to evaluate efforts to engage the public in environmental decisions (Beierle and Cayford, 2002; National Research Council, 2008).

Archival studies are another example of qualitative research. They in-

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Suggested Citation:"Appendix A: Selected Major Social Science Research Methods: Overview." National Research Council. 2012. Using Science as Evidence in Public Policy. Washington, DC: The National Academies Press. doi: 10.17226/13460.

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volve applying a model based on past evidence or decisions to a behavior or intervention for purposes of predicting future behavior (see, e.g., Institute of Medicine, 2010). Archival data may include public data sets collected by academic institutions or government agencies, such as Supreme Court records and corporate filings, or private data sets, such as medical records collected by public or private organizations.

Qualitative research allows for a rich assessment of respondents, often unattainable in other types of studies (Institute of Medicine, 2010). Like some quantitative observational studies, they can provide the rich context in which public policy can benefit society.

THE FUTURE: NEW SOURCES OF DATA

Advances in social science and in computing technology have generated a wealth and diversity of data sources. Although privacy and proprietary concerns pose ongoing challenges for the accessibility of these sources to researchers, the data represent tremendous potential and opportunities to study social phenomena in unprecedented ways.

Federal, state, and local governments collect administrative data on populations as a by-product of program responsibilities, such as the employment history data maintained by the Social Security Administration and the personal income and wealth data maintained by the Internal Revenue Service. There are health records, school records, land-use records, and much more. A growing interest in improving and using administrative records for scientific and policy purposes has generated increased attention to the issues of privacy, data sharing, data quality, and representativeness that have been central to census and survey data for decades.

The challenges and opportunities are even more pronounced with regard to digital data. With the rise and diffusion of advanced information, communication, and computing technologies, an astounding quantity of electronic data—from demographic and geographic variables to transaction records—is amassed at an exponential rate (see Prewitt, 2010). Though much of it is commercially collected and thus proprietary, the vast reservoir of digital data increasingly includes data collected by government agencies for public use. With respect to data quality, use is constrained by the relative brevity of the time series available for variables for which collection began only recently, as well as the fact that the definitions of variables are constantly changing.

The sheer quantity and diversity of digital data with the potential for

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Suggested Citation:"Appendix A: Selected Major Social Science Research Methods: Overview." National Research Council. 2012. Using Science as Evidence in Public Policy. Washington, DC: The National Academies Press. doi: 10.17226/13460.

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social scientific use is astounding. As examples, consider continuous-time location data from cell phones; health data from electronic medical records and monitoring devices; consumer data from credit card transactions, online product searches and purchases, and product radio-frequency identification; satellite imagery and other forms of geocoded data; and data from social networking and other forms of social media.

The increasing “democratization of data” will enable policy analysts and policy makers to obtain much information for themselves, and it will continue to open new frontiers for social scientists. Automated information extraction and text mining have the potential to extract relevant data from the unstructured text of emails, social media posts, speeches, government reports, product reviews, and other web content. Crowd sourcing can be done through extracting information from social network websites. Longitudinal data can be compiled on millions of people with information on their locations, financial transactions, and communications. The data can be analyzed with methods of the emerging field of computational social science: network analysis, geospatial analysis, complexity models, and system dynamics, agent-based, and other social simulation models. Researchers and interested policy actors have only begun to scratch the surface of the potential of new data sources to contribute to policy making (King, 2011).

REFERENCES

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Box, G.E.P., and Draper, N.R. (1969). Evolutionary Operation: A Statistical Method for Process Improvement. New York: Wiley.

Box, G.E.P., and Wilson, K.B. (1951). On the experimental attainment of optimum conditions (with discussion). Journal of the Royal Statistical Society, Series B, 13(1), 1-45.

Campbell, D.T., and Ross, H.L. (1968). The Connecticut crackdown on speeding: Time series data in quasi-experimental analysis. Law and Society Review, 3(1), 33-54.

Campbell, D.T., and Stanley, J.C. (1963). Experimental and Quasi-Experimental Designs for Research. Boston, MA: Houghton Mifflin.

Center on the Developing Child at Harvard University. (2007). A Science-Based Framework for Early Childhood Policy: Using Evidence to Improve Outcomes in Learning, Behavior, and Health for Vulnerable Children. Available: http://developingchild.harvard.edu/fles/7612/5020/4152/Policy_Framework.pdf [August 2012].

Coburn, C.E., Toure, J., and Yamashita, M. (2009). Evidence, interpretation, and persuasion: Instructional decision making at the district central office. Teachers College Record, 111(4), 1,115-1,161.

Cooper, H.M. (2010). Research Synthesis and Meta-Analysis: A Step-by-Step Approach (fourth edition). Thousand Oaks, CA: Sage.

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Cooper, H.M., Hedges, L.V., and Valentine, J.C. (Eds.). (2009). The Handbook of Research Synthesis (second edition). New York: Russell Sage Foundation.

Dominici, F., Zeger, S.L., and Samet, J.M. (1999). Combining evidence on air pollution and daily mortality from the largest 20 U.S. cities: A hierarchical modeling strategy (with discussion). Journal of the Royal Statistical Society, Series A, 163, 263-302.

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Fienberg, S.E., Singer, B., and Tanur, J. (1985). Large-scale social experimentation in the United States. In A.C. Atkinson and S.E. Fienberg (Eds.), A Celebration of Statistics: The ISI Centenary Volume (pp. 287-326). New York: Springer Verlag.

George, A.L. (1979). Case studies and theory development: The method of structured, focused comparison. In P.G. Lauren (Ed.), Diplomacy: New Approaches in History, Theory, and Policy. New York: The Free Press.

George, A.L., and Bennett, A. (2005). Case Studies and Theory Development in the Social Sciences. Cambridge, MA: MIT Press.

Goodman, A., Joyce, R., and Smith, J.P. (2012). The long shadow cast by childhood physical and mental problems on adult life. Proceedings of the National Academy of Sciences, 108, 6,032-6,037.

Greenberg, D., and Shroder, M. (2004). The Digest of Social Experiments (third edition). Washington, DC: Urban Institute Press.

Hedges, L.V., and Olkin, I. (1985). Statistical Methods for Meta-Analysis. San Diego, CA: Academic Press.

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Kellam, S.G., Reid, J., and Balster, R.L. (2008). Effects of a universal classroom behavior program in first and second grades on young adult problem outcomes, Drug and Alcohol Dependence, 95, S1-S4.

King, G. (2011). Ensuring the data-rich future of the social sciences. Science, 331(6,018), 719-721.

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National Research Council. (2002). The Drama of the Commons. Committee on the Human Dimensions of Global Change, E. Ostrom, T. Dietz, N. Dolsak, P.C. Stern, S. Stonich, and E.U. Weber, Eds. Committee on the Human Dimensions of Global Change, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

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National Research Council. (2008). Public Participation in Environmental Assessment and Decision Making. Panel on Public Participation in Environmental Assessment and Decision Making, T. Dietz and P.C. Stern, Eds. Committee on the Human Dimensions of Global Change, Division of Behavioral and Social Sciences and Education. Washington, DC: The National Academies Press.

Neuenschwander, B., Capkun-Niggli, G., Branson, M., and Spiegelhalter, D.J. (2010). Summarizing historical information on controls in clinical trials. Clinical Trials, 7(1), 5-18.

Ostrom, E. (1990). Governing the Commons: The Evolution of Institutions for Collective Action. New York: Cambridge University Press.

Prewitt, K. (2010). Science starts not after measurement but with measurement. The Annals of the American Academy of Political and Social Sciences, 631(1), 7-13.

Stern, P.C., and Druckman, D. (2000). Evaluating interventions in history: The case of international conflict resolution. International Studies Review, 2(1), 33-63.

Turner, R.M., Spiegelhalter, D.J., Smith, G.C.S., and Thompson, S.G. (2009). Bias modelling in evidence synthesis. Journal of the Royal Statistical Society, Series A, 172, 23-47.

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Suggested Citation:"Appendix A: Selected Major Social Science Research Methods: Overview." National Research Council. 2012. Using Science as Evidence in Public Policy. Washington, DC: The National Academies Press. doi: 10.17226/13460.

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FAQs

How is science used in public policy? ›

Science offers solutions to problems, in some instances extending to policy design and implementation, from improved weapons systems to public health to school reform. Science also predicts the likely outcomes of particular policy actions and then evaluates those outcomes, intended and unintended, wanted and unwanted.

Why is science important to public policy? ›

There is science used for developing public policy, as part of the decision-making process to create laws related to problems such as water quality and clean air (science for policy).

What is the relationship between science and policy? ›

Scientists produce evidence, which policy makers then use for decisions. In return, policy makers provide scientists with evidence requirements and resources for research.

What is science according to McGinn 1991? ›

McGinn posits that. we could begin to understand science as "knowledge", "a field of system. atic inquiry into nature", "a form of human cultural activity", and "a total of. societal enterprise" (emphases ours).

What is the relationship between science technology and public policy? ›

science and technology influence public policy; public policy influences the evolution of science and technology; the outcomes of these interactions affect well-being in the United States and worldwide; the processes involved can be made more effective and their outcomes more beneficial.

What is the role of science and technology in policy making? ›

In sum, the role of science in policy development is to do the following: Provide an evidence base for decisions; Confirm the soundness of a policy in areas in which the evidence is conclusive; Define the contours of uncertainty and trade-offs when the likely outcomes cannot be known for sure; and.

What are science based policies? ›

Science policy focuses on knowledge production and role of knowledge networks, collaborations, and the complex distributions of expertise, equipment, and know-how. Understanding the processes and organizational context of generating novel and innovative science and engineering ideas is a core concern of science policy.

What do you mean by science policy? ›

Science policy is defined as being an area of public policy which is concerned with the policies that affect the conduct of the science and research enterprise…often in pursuance of other national policy goals such as technological innovation, weapons development, health care and environmental monitoring.

Does political science link to public policy? ›

Definitions. Political Science is the study of governments, public policies and political processes, systems, and political behavior.

What is the difference between policy for science and science for policy? ›

Harvey Brooks (1964) characterized this relation as twofold: Science for policy refers to the use of knowledge to facilitate or improve decision making; policy for science refers to decision making about how to fund or structure the systematic pursuit of knowledge.

When was the first policy related to science and technology introduced? ›

Likewise, the first policy relating to Science and Technology was first introduced in 1958. Over the recent past, India declared the decade 2010-2020 as the “Decade of Innovation.”

What are the 4 meaning of science according to McGinn? ›

According to McGinn (1991) Science has four meanings: As a Knowledge : the organized, well-founded body of knowledge of natural phenomena. As a Field of Systematic Inquiry into Nature : the particular field or domain or systematic inquiry in which such knowledge is sought.

What is science according to Popper? ›

Science is about falsification not confirmation of a hypothesis. Popper believed a good idea could be tested with the risk of being wrong, which lead to more knowledge than one which could not be tested but claimed to explain everything. Essentially, we learn from our mistakes.

What is the 3 main goal of science education? ›

Remember that the goal of science education is to teach students to: Use and interpret science to explain the world around them. Evaluate and understand scientific theories and evidence. Investigate and generate scientific explanations.

What are the important roles do science and technology plays on general public? ›

Science and technology have made it easier for people to communicate with other people across the world. They also helped in decreasing the costs of production leading to business growth as well as contributing to the development in the agriculture sector, education sector, and industrial/manufacturing sector.

Is public policy part of social science? ›

While there are degrees in public policy, public policy in itself is not defined as a social science, but instead uses various forms of social sciences, such as political science, economics, and psychology to develop its evidence base for policy development.

What is the main relationship between science technology and society? ›

The essence of how science and technology contributes to society is the creation of new knowledge, and then utilization of that knowledge to boost the prosperity of human lives, and to solve the various issues facing society.

Is policy making an art or a science? ›

Many years in practical policy making show that it is part science and part art. Complex systems science, as a form of story telling, can create links between them.

What are the 10 benefits of science? ›

10 Reasons Why Science Is Important
  • #2. Science teaches you how to solve problems. ...
  • #3. Science has many benefits for young students. ...
  • #4. Science helps us live longer. ...
  • #5. Science reduces child mortality. ...
  • #6. Science led to the creation of technologies we use every day. ...
  • #7. Science can combat climate change. ...
  • #8. ...
  • #9.
1 Oct 2021

What are 2 benefits of science? ›

The advantages of Science and Technology are:
  • It will make our life easier.
  • It helps us organize our daily activities.
  • This helps our work can be done faster.
  • It helps us to communicate more easily with others.
  • This helps us to better know and understand other cultures and societies.

What is the main importance of science? ›

Science is valued by society because the application of scientific knowledge helps to satisfy many basic human needs and improve living standards. Finding a cure for cancer and a clean form of energy are just two topical examples.

What are the 4 types of policy? ›

The four main types of public policy include regulatory policy, constituent policy, distributive policy, and redistributive policy. These four policy types differ in terms of what their goals are, and who they impact or benefit.

What are 5 main rules in science? ›

What are the five scientific laws? The five most popular scientific laws are Hooke's Law of Elasticity, Archimedes' Principle of Buoyancy, Dalton's Law of Partial Pressures, Bernoulli's Law of Fluid Dynamics and Fourier's Law of Heat Conduction.

What are the 3 types of policy? ›

Public policy can be studied as producing three types of policies (distributive, regulatory and re-distributive) related with decision making process.

Who is called the father of policy science? ›

Aristotle is called the father of political science because he elaborated on the topics and thinking of the Ideal State, slavery, revolution, education, citizenship, forms of government, the theory of golden mean, theory of constitution etc.

Who started policy science? ›

Policy Sciences is a quarterly peer-reviewed academic journal covering issues and practices in the policy studies. It was established in 1970 and is published by Springer Science+Business Media on behalf of the Society of Policy Scientists.

What is the focus of public policy? ›

Public policy focuses on the decisions that create the outputs of a political system, such as transport policies, the management of a public health service, the administration of a system schooling and the organization of a defense force.

Why is social science policy more difficult than natural science policy? ›

Because they deal with systems that are highly complex, adaptive and not rigorously rule-bound, the social sciences are among the most difficult of disciplines, both methodologically and intellectually.

What is the difference between political science and public policy? ›

Political science is a broad field of study in the social sciences that focuses on systems of government and the analysis of political activities and behaviors. Public policy is a branch of political science that addresses public concerns and problems.

What are the different government policies for science and technology explain any 3? ›

Four major policies have been implemented since independence namely, Scientific Policy Resolution (SPR 1958), Technology Policy Statement 1983 (SPR 1958), Science and Technology Policy 2003 (STP 2003), and Science Technology Innovation Policy 2013 (STIP 2013), this article will attempt to give a retrospective on how ...

What is the main policy goal for the new Science Technology and innovation policy? ›

The new Science, Technology, Innovation Policy aims to bring about profound changes through short-term, medium-term, and long-term mission mode projects by building a nurtured ecosystem that promotes research and innovation on the part of both individuals and organizations.

What is science technology and innovation policy? ›

The Government of India will launch its 5th National Science, Technology and Innovation Policy, a holistic and pragmatic policy dedicated to Science, technology, and most importantly innovation. The policy aims to reorient Science Technology & Innovation (STI) in terms of priorities, sectoral focus, and strategies.

What are the national policy on science and technology 1986? ›

The first National Science and Technology Policy in the country was produced in 1986. The policy was designed to create harmony in the pursuit of knowledge about the environment through Research and Development (R&D). The aim was to use S&T knowledge to ensure a better quality of life for the people.

What is the importance of science in our Life explain in 4/5 sentences? ›

Science is involved in cooking, eating, breathing, driving, playing, etc. The fabric we wear, the brush and paste we use, the shampoo, the talcum powder, the oil we apply, everything is the consequence of advancement of science. Life is unimaginable without all this, as it has become a necessity.

What are the 4 aims of science? ›

The main objectives of science are: To understand the functional role of nature and explain it in a complete form. To provide knowledge of the laws of nature after verifying them by experiments. To control nature by the applications of results of experiments performed through keen observation.

What are the 4 key aspects of science? ›

The four major branches of science are, Mathematics and logic, biological science, physical science, and social science.

What is the real definition of science? ›

Science is the pursuit and application of knowledge and understanding of the natural and social world following a systematic methodology based on evidence. Scientific methodology includes the following: Objective observation: Measurement and data (possibly although not necessarily using mathematics as a tool) Evidence.

What was Karl Popper's main contribution to science? ›

Popper's principal contribution to the philosophy of science rests on his rejection of the inductive method in the empirical sciences. According to this traditional view, a scientific hypothesis may be tested and verified by obtaining the repeated outcome of substantiating observations.

What does CS Lewis say about science? ›

He regards science, properly speaking, as a subset of religion. He believes science to be a fundamentally imaginative enterprise. He argues that scientific statements, because they tend to be univocal and strive to be verifiable, are actually rather small statements, all things considered.

What are the 2 main goals of science? ›

The goals of science are to answer questions through research and evidence.

What is the first goal of science? ›

The first and most basic goal of science is to describe. This goal is achieved by making careful observations.

What is a smart goal for science? ›

For those of you who are unaware of SMART goals, SMART standards for Specific, Measurable, Attainable, Realistic, and Time-Bound. They're the five criteria that you should ensure that all of your goals meet in order to have a chance of meeting them successfully.

How is the scientific method used in political science? ›

Like other social sciences, political science uses a "scientific" approach, meaning that political scientists approach their study in an objective, rational, and systematic manner. Some political scientists focus on abstract and theoretical questions, while others study particular government policies and their effects.

What is the science in politics? ›

Political science focuses on the theory and practice of government and politics at the local, state, national, and international levels. We are dedicated to developing understandings of institutions, practices, and relations that constitute public life and modes of inquiry that promote citizenship.

Can the scientific method be applied to politics? ›

The scientific method, in which findings are based on objective, systematic observation and verified through public inspection of methods and results, is the dominant methodological approach in political science.

What are the 4 types of public policy? ›

The three types of public policies are regulatory, restrictive, and facilitating policies. In addition, there are two types of restrictions, economic, and public.

What are the 3 types of public policy? ›

Public policy can be studied as producing three types of policies (distributive, regulatory and re-distributive) related with decision making process.

What are the 5 methods of political science? ›

Political scientists rely on a variety of empirical methods and statistical models, such as linear regression, maximum likelihood estimation, laboratory and survey experiments, and social network analysis. Mathematical models are also important tools for rigorous theoretical analysis.

Who first used scientific method in political science? ›

Some have identified Plato (428/427–348/347 bce), whose ideal of a stable republic still yields insights and metaphors, as the first political scientist, though most consider Aristotle (384–322 bce), who introduced empirical observation into the study of politics, to be the discipline's true founder.

What are 3 importance of the scientific method? ›

It provides an objective, standardized approach to conducting experiments and, in doing so, improves their results. By using a standardized approach in their investigations, scientists can feel confident that they will stick to the facts and limit the influence of personal, preconceived notions.

Who said that politics is a science? ›

Ancient. The antecedents of Western politics can be traced back to the Socratic political philosophers, such as Aristotle ("The Father of Political Science") (384–322 BC). Aristotle was one of the first people to give a working definition of political science.

What are the 6 types of political science? ›

Fields of Study
  • American Politics. ...
  • Comparative Politics. ...
  • Political Theory. ...
  • International Relations. ...
  • Political Behavior. ...
  • Political Methodology.

What are the example of political science? ›

Political scientists study domestic and foreign policy. We study power processes between people and countries, but we also study the relationships within and between, for example, non-governmental organizations and political parties.

What is the importance of scientific method as applied to society? ›

The Scientific Method is not the only way, but is the best-known way to discover how and why the world works, without our knowledge being tainted by religious, political, or philosophical values. This method provides a means to formulate questions about general observations and devise theories of explanation.

How does political science influence our society? ›

Its goal is to deepen human understanding of the forms and nature of political action and to develop theoretical tools for interpreting politically meaningful phenomena. The discipline deals with the traditional fields of public national life, such as democracy, parliaments, politicians, elections and the government.

Who said that political science is not a science? ›

Answer and Explanation: It was psychologist Philip E. Tetlock, in the 1980s, who claimed that political science isn't a science after he found that political scientists were not able to forecast the future accurately than chimps randomly throwing darts at multiple outcomes.

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