In science what kind of ideas are generally accepted

Two methods of logical thinking are used: inductive reasoning and deductive reasoning. Inductive reasoning is a form of logical thinking that uses related observations to arrive at a general conclusion. This type of reasoning is common in descriptive science. A life scientist such as a biologist makes observations and records them. These data can be qualitative descriptive or quantitative consisting of numbers , and the raw data can be supplemented with drawings, pictures, photos, or videos.

From many observations, the scientist can infer conclusions inductions based on evidence. Inductive reasoning involves formulating generalizations inferred from careful observation and the analysis of a large amount of data. Brain studies often work this way. Many brains are observed while people are doing a task.

The part of the brain that lights up, indicating activity, is then demonstrated to be the part controlling the response to that task. Deductive reasoning or deduction is the type of logic used in hypothesis-based science. In deductive reasoning, the pattern of thinking moves in the opposite direction as compared to inductive reasoning.

Deductive reasoning is a form of logical thinking that uses a general principle or law to forecast specific results. From those general principles, a scientist can extrapolate and predict the specific results that would be valid as long as the general principles are valid.

For example, a prediction would be that if the climate is becoming warmer in a region, the distribution of plants and animals should change. Comparisons have been made between distributions in the past and the present, and the many changes that have been found are consistent with a warming climate. Finding the change in distribution is evidence that the climate change conclusion is a valid one. Both types of logical thinking are related to the two main pathways of scientific study: descriptive science and hypothesis-based science.

Descriptive or discovery science aims to observe, explore, and discover, while hypothesis-based science begins with a specific question or problem and a potential answer or solution that can be tested. The boundary between these two forms of study is often blurred, because most scientific endeavors combine both approaches.

Observations lead to questions, questions lead to forming a hypothesis as a possible answer to those questions, and then the hypothesis is tested. Thus, descriptive science and hypothesis-based science are in continuous dialogue. Biologists study the living world by posing questions about it and seeking science-based responses. This approach is common to other sciences as well and is often referred to as the scientific method.

The scientific method is not exclusively used by biologists but can be applied to almost anything as a logical problem-solving method.

The scientific process typically starts with an observation often a problem to be solved that leads to a question. One Monday morning, a student arrives at class and quickly discovers that the classroom is too warm. That is an observation that also describes a problem: the classroom is too warm.

Recall that a hypothesis is a suggested explanation that can be tested. To solve a problem, several hypotheses may be proposed. Once a hypothesis has been selected, a prediction may be made. A hypothesis must be testable to ensure that it is valid. For example, a hypothesis that depends on what a bear thinks is not testable, because it can never be known what a bear thinks.

It should also be falsifiable, meaning that it can be disproven by experimental results. To test a hypothesis, a researcher will conduct one or more experiments designed to eliminate one or more of the hypotheses. This is important. A hypothesis can be disproven, or eliminated, but it can never be proven.

Science does not deal in proofs like mathematics. If an experiment fails to disprove a hypothesis, then we find support for that explanation, but this is not to say that down the road a better explanation will not be found, or a more carefully designed experiment will be found to falsify the hypothesis. Each experiment will have one or more variables and one or more controls. A variable is any part of the experiment that can vary or change during the experiment. A control is a part of the experiment that does not change.

Look for the variables and controls in the example that follows. As a simple example, an experiment might be conducted to test the hypothesis that phosphate limits the growth of algae in freshwater ponds.

A series of artificial ponds are filled with water and half of them are treated by adding phosphate each week, while the other half are treated by adding a salt that is known not to be used by algae. The variable here is the phosphate or lack of phosphate , the experimental or treatment cases are the ponds with added phosphate and the control ponds are those with something inert added, such as the salt. Just adding something is also a control against the possibility that adding extra matter to the pond has an effect.

If the treated ponds show lesser growth of algae, then we have found support for our hypothesis. If they do not, then we reject our hypothesis. Be aware that rejecting one hypothesis does not determine whether or not the other hypotheses can be accepted; it simply eliminates one hypothesis that is not valid.

Using the scientific method, the hypotheses that are inconsistent with experimental data are rejected. In the example below, the scientific method is used to solve an everyday problem. However, each experiment is based on conclusions from prior studies; repeated failure of the experiment eventually calls into question those conclusions and leads to reevaluation of the measurements, generality, design, and interpretation of the earlier work. Thus publication of a scientific report provides an opportunity for the community at large to critique and build on the substance of the report, and serves as one stage at which errors and misinterpretations can be detected and corrected.

Each new finding is considered by the community in light of what is already known about the system investigated, and disagreements with established measurements and interpretations must be justified. For example, a particular interpretation of an electrical measurement of a material may implicitly predict the results of an optical experiment.

If the reported optical results are in disagreement with the electrical interpretation, then the latter is unlikely to be correct—even though the measurements them-. It is also possible, however, that the contradictory results are themselves incorrect, and this possibility will also be evaluated by the scientists working in the field.

It is by this process of examination and reexamination that science advances. The research endeavor can therefore be viewed as a two-tiered process: first, hypotheses are formulated, tested, and modified; second, results and conclusions are reevaluated in the course of additional study.

In fact, the two tiers are interrelated, and the goals and traditions of science mandate major responsibilities in both areas for individual investigators. Importantly, the principle of self-correction does not diminish the responsibilities of the investigator in either area. The investigator has a fundamental responsibility to ensure that the reported results can be replicated in his or her laboratory.

The scientific community in general adheres strongly to this principle, but practical constraints exist as a result of the availability of specialized instrumentation, research materials, and expert personnel. Other forces, such as competition, commercial interest, funding trends and availability, or pressure to publish may also erode the role of replication as a mechanism for fostering integrity in the research process.

The panel is unaware of any quantitative studies of this issue. The process of reevaluating prior findings is closely related to the formulation and testing of hypotheses. In that setting, the precise replication of a prior result commonly serves as a crucial control in attempts to extend the original findings.

It is not unusual that experimental flaws or errors of interpretation are revealed as the scope of an investigation deepens and broadens. If new findings or significant questions emerge in the course of a reevaluation that affect the claims of a published report, the investigator is obliged to make public a correction of the erroneous result or to indicate the nature of the questions. Occasionally, this takes the form of a formal published retraction, especially in situations in which a central claim is found to be fundamentally incorrect or irreproducible.

More commonly, a somewhat different version of the original experiment, or a revised interpretation of the original result, is published as part of a subsequent report that extends in other ways the initial work.

Such behavior is, at best, a questionable research practice. Clearly, each scientist has a responsibility to foster an environment that en-. Much greater complexity is encountered when an investigator in one research group is unable to confirm the published findings of another.

In such situations, precise replication of the original result is commonly not attempted because of the lack of identical reagents, differences in experimental protocols, diverse experimental goals, or differences in personnel. Under these circumstances, attempts to obtain the published result may simply be dropped if the central claim of the original study is not the major focus of the new study.

Alternatively, the inability to obtain the original finding may be documented in a paper by the second investigator as part of a challenge to the original claim. In any case, such questions about a published finding usually provoke the initial investigator to attempt to reconfirm the original result, or to pursue additional studies that support and extend the original findings.

In accordance with established principles of science, scientists have the responsibility to replicate and reconfirm their results as a normal part of the research process. The cycles of theoretical and methodological formulation, testing, and reevaluation, both within and between laboratories, produce an ongoing process of revision and refinement that corrects errors and strengthens the fabric of research.

The panel defined a mentor as that person directly responsible for the professional development of a research trainee. The relationship of the mentor and research trainee is usually characterized by extraordinary mutual commitment and personal involvement. A mentor, as a research advisor, is generally expected to supervise the work of the trainee and ensure that the trainee's research is completed in a sound, honest, and timely manner.

The ideal mentor challenges the trainee, spurs the trainee to higher scientific achievement, and helps socialize the trainee into the community. Research mentors thus have complex and diverse roles. Many individuals excel in providing guidance and instruction as well as personal support, and some mentors are resourceful in providing funds and securing professional opportunities for their trainees.

The mentoring relationship may also combine elements of other relationships, such as parenting, coaching, and guildmastering. Many students come to respect and admire their mentors, who act as role models for their younger colleagues. However, the mentoring relationship does not always function properly or even satisfactorily.

Almost no literature exists that evaluates which problems are idiosyncratic and which are systemic. However, it is clear that traditional practices in the area of mentorship and training are under stress.

In some research fields, for example, concerns are being raised about how the increasing size and diverse composition of research groups affect the quality of the relationship between trainee and mentor. As the size of research laboratories expands, the quality of the training environment is at risk CGS, a. Large laboratories may provide valuable instrumentation and access to unique research skills and resources as well as an opportunity to work in pioneering fields of science.

But as only one contribution to the efforts of a large research team, a graduate student's work may become highly specialized, leading to a narrowing of experience and greater dependency on senior personnel; in a period when the availability of funding may limit research opportunities, laboratory heads may find it necessary to balance research decisions for the good of the team against the individual educational interests of each trainee.

Moreover, the demands of obtaining sufficient resources to maintain a laboratory in the contemporary research environment often separate faculty from their trainees. When laboratory heads fail to participate in the everyday workings of the laboratory—even for the most beneficent of reasons, such as finding funds to support young investigators—their inattention may harm their trainees' education.

Although the size of a research group can influence the quality of mentorship, the more important issues are the level of supervision received by trainees, the degree of independence that is appropriate for the trainees' experience and interests, and the allocation of credit for achievements that are accomplished by groups composed of individuals with different status.

Certain studies involving large groups of 40 to or more are commonly carried out by collaborative or hierarchical arrangements under a single investigator. These factors may affect the ability of research mentors to transmit the methods and ethical principles according to which research should be conducted.

Problems also arise when faculty members are not directly rewarded for their graduate teaching or training skills. Although faculty may receive indirect rewards from the contributions of well-trained graduate students to their own research as well as the satisfaction of seeing their students excelling elsewhere, these rewards may not be sufficiently significant in tenure or promotion decisions. When institutional policies fail to recognize and reward the value of good teaching and mentorship, the pressures to maintain stable funding for research teams in a competitive environment can overwhelm the time allocated to teaching and mentorship by a single investigator.

The increasing duration of the training period in many research fields is another source of concern, particularly when it prolongs the dependent status of the junior investigator. The formal period of graduate and postdoctoral training varies considerably among fields of study.

In , the median time to the doctorate from the baccalaureate degree was 6. The disciplinary median varied: 5. Students, research associates, and faculty are currently raising various questions about the rights and obligations of trainees. Sexist behavior by some research directors and other senior scientists is a particular source of concern. Another significant concern is that research trainees may be subject to exploitation because of their subordinate status in the research laboratory, particularly when their income, access to research resources, and future recommendations are dependent on the goodwill of the mentor.

Foreign students and postdoctoral fellows may be especially vulnerable, since their immigration status often depends on continuation of a research relationship with the selected mentor. Inequalities between mentor and trainee can exacerbate ordinary conflicts such as the distribution of credit or blame for research error NAS, When conflicts arise, the expectations and assumptions.

Ideally, mentors and trainees should select each other with an eye toward scientific merit, intellectual and personal compatibility, and other relevant factors.

But this situation operates only under conditions of freely available information and unconstrained choice —conditions that usually do not exist in academic research groups. The trainee may choose to work with a faculty member based solely on criteria of patronage, perceived influence, or ability to provide financial support.

Good mentors may be well known and highly regarded within their research communities and institutions. Unfortunately, individuals who exploit the mentorship relationship may be less visible. Poor mentorship practices may be self-correcting over time, if students can detect and avoid research groups characterized by disturbing practices.

However, individual trainees who experience abusive relationships with a mentor may discover only too late that the practices that constitute the abuse were well known but were not disclosed to new initiates. It is common practice for a graduate student to be supervised not only by an individual mentor but also by a committee that represents the graduate department or research field of the student.

However, departmental oversight is rare for the postdoctoral research fellow. In order to foster good mentorship practices for all research trainees, many groups and institutions have taken steps to clarify the nature of individual and institutional responsibilities in the mentor—trainee relationship. The self-regulatory system that characterizes the research process has evolved from a diverse set of principles, traditions, standards, and customs transmitted from senior scientists, research directors, and department chairs to younger scientists by example, discussion, and informal education.

The principles of honesty, collegiality, respect for others, and commitment to dissemination, critical evaluation, and rigorous training are characteristic of all the sciences. Methods and techniques of experimentation, styles of communicating findings,. Within those disciplines, practices combine the general with the specific. Ideally, research practices reflect the values of the wider research community and also embody the practical skills needed to conduct scientific research.

Practicing scientists are guided by the principles of science and the standard practices of their particular scientific discipline as well as their personal moral principles. But conflicts are inherent among these principles. For example, loyalty to one's group of colleagues can be in conflict with the need to correct or report an abuse of scientific practice on the part of a member of that group.

Because scientists and the achievements of science have earned the respect of society at large, the behavior of scientists must accord not only with the expectations of scientific colleagues, but also with those of a larger community.

As science becomes more closely linked to economic and political objectives, the processes by which scientists formulate and adhere to responsible research practices will be subject to increasing public scrutiny. This is one reason for scientists and research institutions to clarify and strengthen the methods by which they foster responsible research practices. The panel believes that the existing self-regulatory system in science is sound.

But modifications are necessary to foster integrity in a changing research environment, to handle cases of misconduct in science, and to discourage questionable research practices. Individual scientists have a fundamental responsibility to ensure that their results are reproducible, that their research is reported thoroughly enough so that results are reproducible, and that significant errors are corrected when they are recognized.

Editors of scientific journals share these last two responsibilities. Research mentors, laboratory directors, department heads, and senior faculty are responsible for defining, explaining, exemplifying, and requiring adherence to the value systems of their institutions. The neglect of sound training in a mentor's laboratory will over time compromise the integrity of the research process. Administrative officials within the research institution also bear responsibility for ensuring that good scientific practices are observed in units of appropriate jurisdiction and that balanced reward systems appropriately recognize research quality, integrity, teaching, and mentorship.

Adherence to scientific principles and disciplinary standards is at the root of a vital and productive research environment. At present, scientific principles are passed on to trainees primarily by example and discussion, including training in customary practices. Most research institutions do not have explicit programs of instruction and discussion to foster responsible research practices, but the communication of values and traditions is critical to fostering responsible research practices and detering misconduct in science.

Efforts to foster responsible research practices in areas such as data handling, communication and publication, and research training and mentorship deserve encouragement by the entire research community.

Problems have also developed in these areas that require explicit attention and correction by scientists and their institutions. If not properly resolved, these problems may weaken the integrity of the research process. Several excellent books on experimental design and statistical methods are available. See, for example, Wilson and Beveridge For a somewhat dated review of codes of ethics adopted by the scientific and engineering societies, see Chalk et al.

Selected examples of academic research conduct policies and guidelines are included in Volume II of this report. See also Holton See, for example, responses to the Proceedings of the National Academy of Sciences action against Friedman: Hamilton and Abelson et al. See also the discussion in Bailar et al.

See, for example, Culliton and Bradshaw et al. For the impact of the inability to provide corroborating data or witnesses, also see Ross et al. See, for example, the discussion on random data audits in Institute of Medicine a , pp. For a full discussion of the practices and policies that govern authorship in the biological sciences, see Bailar et al.

Note that these general guidelines exclude the provision of reagents or facilities or the supervision of research as a criteria of authorship. A full discussion of problematic practices in authorship is included in Bailar et al. A controversial review of the responsibilities of co-authors is presented by Stewart and Feder In the past, scientific papers often included a special note by a named researcher, not a co-author of the paper, who described, for example, a particular substance or procedure in a footnote or appendix.

This practice seems to. Angell advocates closer coordination between institutions and editors when institutions have ascertained misconduct. Deposition is important for data that cannot be directly printed because of large volume. For more complete discussions of peer review in the wider context, see, for example, Cole et al. The strength of theories as sources of the formulation of scientific laws and predictive power varies among different fields of science.

For example, theories derived from observations in the field of evolutionary biology lack a great deal of predictive power. The role of chance in mutation and natural selection is great, and the future directions that evolution may take are essentially impossible to predict. Theory has enormous power for clarifying understanding of how evolution has occurred and for making sense of detailed data, but its predictive power in this field is very limited.

See, for example, Mayr , Much of the discussion on mentorship is derived from a background paper prepared for the panel by David Guston. Although the time to the doctorate is increasing, there is some evidence that the magnitude of the increase may be affected by the organization of the cohort chosen for study.

In the humanities, the increased time to the doctorate is not as large if one chooses as an organizational base the year in which the baccalaureate was received by Ph. Some universities have written guidelines for the supervision or mentorship of trainees as part of their institutional research policy guidelines see, for example, the guidelines adopted by Harvard University and the University of Michigan that are included in Volume II of this report.

The guidelines often affirm the need for regular, personal interaction between the mentor and the trainee. They indicate that mentors may need to limit the size of their laboratories so that they are able to interact directly and frequently with all of their trainees.

Although there are many ways to ensure responsible mentorship, methods that provide continuous feedback, whether through formal or informal mechanisms, are apt to be the most successful CGS, a.

Departmental mentorship awards comparable to teaching or research prizes can recognize, encourage, and enhance the. Others have noted that although it may be desirable to limit the number of trainees assigned to a senior investigator, there is insufficient information at this time to suggest that numbers alone significantly affect the quality of research supervision IOM, a, p. Responsible Science is a comprehensive review of factors that influence the integrity of the research process.

Volume I examines reports on the incidence of misconduct in science and reviews institutional and governmental efforts to handle cases of misconduct. The result of a two-year study by a panel of experts convened by the National Academy of Sciences, this book critically analyzes the impact of today's research environment on the traditional checks and balances that foster integrity in science.

Responsible Science is a provocative examination of the role of educational efforts; research guidelines; and the contributions of individual scientists, mentors, and institutional officials in encouraging responsible research practices. Based on feedback from you, our users, we've made some improvements that make it easier than ever to read thousands of publications on our website.

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Get This Book. Visit NAP. Looking for other ways to read this? No thanks. Page 37 Share Cite. Physicist Richard Feynman invoked the informal approach to communicating the basic principles of science in his commencement address at the California Institute of Technology Feynman, : [There is an] idea that we all hope you have learned in studying science in school—we never explicitly say what this is, but just hope that you catch on by all the examples of scientific investigation.

Page 38 Share Cite. Page 39 Share Cite. Page 40 Share Cite. Page 41 Share Cite. Individual Scientific Disciplines. Page 42 Share Cite. Page 43 Share Cite. Institutional Policies. They then make a testable prediction, test this prediction over and over and over , and analyze the data. Once this is done, they can then state whether or not their hypothesis was correct.

Even then, a hypothesis needs to be tested and retested many times by many different experts before it is generally accepted in the scientific community as being true. Example: You observe that, upon waking up each morning, your trash is overturned and junk is spread around the yard. You form a hypothesis that raccoons are responsible.

Through testing — maybe you stay up all night to watch for raccoons — the results will either support or refute your hypothesis. The above example illustrates why the simulation hypothesis is not science and definitely not a scientific theory. Like the idea of God or an immortal soul, it is beyond the natural world and, so, beyond the realm of science. A scientific theory consists of one or more hypotheses that have been supported by repeated testing. Theories are one of the pinnacles of science and are widely accepted in the scientific community as being true.

A theory must never be shown to be wrong; if it is, the theory is disproven. Theories can also evolve. The evolution from Newtonian physics to general relativity is a good way to explain how new information can cause a theory to evolve into a more complete theory:.

Albert Einstein later discovered the theories of special and general relativity — that the force of gravity exists due to the bending of spacetime, which is caused by massive objects. This created a more complete theory of gravity. He just had a partial answer.