Examine the two articles in The Economist October, 2013 pp. 19-25 on the problems of science. Explain what problems are spelled out, and describe the solutions suggested to address them.

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Examine the two articles in The Economist October, 2013 pp. 19-25 on the problems of science. Explain what problems are spelled out, and describe the solutions suggested to address them.

Category: Rhetorical Analysis Essay

Subcategory: Anatomy

Level: Academic

Pages: 4

Words: 1100

Name of the Student
Professor’s name
Medical Sciences
5th November, 2015
Creative Writing: Article Critique
The two articles published in “The Economist” October 2013, pp.19-25, reflected the issues regarding quality of research, and scientific experiments, carried out all across the globe. Since the development of modern science during the 17th century, there has been a revolution around the globe regarding technological advancements and clinical solutions (“How science goes wrong” 19-25). However, under the present circumstances it is also noted that scientists are not taking adequate measures to verify the outcomes of their experimentation. This means such scientists are just relying on the data they obtained from experimentation, without introspecting its originality or viability (“How science goes wrong” 19-25). Thus, the trust on the findings has superseded the verification process (“How science goes wrong” 19-25). Such issues have led to false claims of an experimentation end point. The amount of research conducted all across the globe has increased manifolds.
Such increase in research activities has been encouraged through financial grants from academic levels and industry partnerships(“How science goes wrong” 19-25). However, the major concern that needs to be addressed is the truth and reproducibility of such experimentation. Often it is noted, that the results of such experiments do not match in subsequent replications (“How science goes wrong” 19-25). This puts a question mark on the integrity of the original and subsequent research. The context of such jeopardy may be attributed to the academic pressure and appraisal norms created in various higher education systems all across the globe. A common philosophy amongst the peers in a higher education system is that, either one should publish or should perish (“How science goes wrong” 19-25). Hence, for their self-existence various researches are carried out without any clear cut goals or endpoints. Scientists are inclined to search for journals with higher impact factors and are tailor making their research to suit the criteria of publication only. They are swayed away from the requirement of science and the research what science demands from that scientist. A plethora of research is being conducted in a very short period, as because the grants are often extended for a limited period of time (“How science goes wrong” 19-25). This is an alarming situation because research cannot be time bound and often the initial protocol has to be reoriented. Perhaps, this is the reason that during the 1950s, when there was not so much career or publication pressure, viable results were obtained through experimentation (“How science goes wrong” 19-25). Such results formed the basis of the technological and clinical advancements that we cherish currently.
However, such space is not being provided by the demand of the academic system. Not only in basic scientific research, but such issues are also taking place in applied researches. For example, data suggested that even in the field of biotechnology research more than half of the experiments or results could not be reproduced (“How science goes wrong” 19-25). This means if a group of scientists claim the viability of a biotechnological advancement, it may very well being negated down by a different group of scientists in subsequent researches. The objective truth of truth is often jeopardized and philosophy of priming or “gut feeling” is put into end analysis (“Trouble at the lab’ 19-25). The alarming situation lies in the rejection of scientific works by peer reviewed journals. Almost 90% of original papers submitted in such peer-reviewed journals are rejected due to non-reproducibility of data, or insufficient information or issues with the protocol of the experimentation (“How science goes wrong” 19-25). Most of the researches that are being conducted in academics are being classified as shoddy experiments or experiments with poor analysis(“How science goes wrong” 19-25). Often such experiments are conducted, because grants or funding are available in that field (“How science goes wrong” 19-25). Even if a scientist or a scholar is inclined to a targeted area of research, he or she cannot pursue owing to a lack of funds (“Trouble at the lab’ 19-25).
Another area that requires attention is the inability of scientists to frame proper statistical hypothesis or statistical analysis of data (“Trouble at the lab’ 19-25). Such issues lead to the incorrect conclusion of various experimental findings and in some cases either the results are exaggerated or underreported (“Trouble at the lab’ 19-25). The issue of intervening proper statistical tests and the hypothesis is of prime importance.
The issue with statistics creeps from the very beginning, regarding the selection of samples. Either sample does not reflect the experimental population, or may suffer from bias, due to a lack of standardization or elimination of confounding variables (Huff 1991). This leads to experimental errors, and the projection of validity of the endpoints comes with several limitations. Often the experimentation is conducted without proper framing of a hypothesis. This leads to wrongful acceptance of Type 1 or Type 2 errors (“Trouble at the lab’ 19-25). Lack of reproducibility of experimental results and improper analysis of statistical data may jeopardize the goals of experimentation, and may be detrimental to human health or technological advancements (“Trouble at the lab’ 19-25). Even for the sake of argument if it is considered that such results of clinical trials or experimental results are not going to impact human health, still a lot of financial wastage or lack of cost-effective strategies will occur(“How science goes wrong” 19-25). This situation is not desirable and specifically in some developing countries, where the basic requirements like the security of food and shelter are still not ensured for all of its citizens.
Therefore to increase the viability of research and judicial use of financial grants, various steps may be implemented from the scientific bodies or grant sanctioning authorities. First of all, enough encouragement should be given to scientists and faculties to carry out repetition research. This would provide an avenue whether to accept finally the end results of previous publication or reject such results robustly (“How science goes wrong” 19-25). Secondly, there should be a standardization of protocols all across the world on a specific trial that may help to provide a uniformity of results (“How science goes wrong” 19-25). Thirdly, the important issue which must be endorsed is the proper utilization and understanding of statistical tests and the hypothesis to be tested. Researchers should be amply clear whether they should opt t o retain a null hypothesis or an alternative hypothesis (Duff 1991). Selection of statistical tests would also be important criteria to ensure experimental findings. Statistical findings must be correlated with clinical findings to provide actual interpretation of data. Since, in some cases the results might not be statistically relevant but is significantly important from the aspect of clinical end points (“Trouble at the lab’ 19-25).
The next issue to minimize experimental errors and to create a bias in a result is to disclose the experimental procedure well in advance (“Trouble at the lab’ 19-25). Further, if the protocol permits the raw data that are collected should be uploaded for various scientists to get access to such data. This would increase the viability of a research since replications of the same experiment may run simultaneously in different laboratories of the world (“How science goes wrong” 19-25). Another aspect that requires great focus is to stand for a statistical test which is insignificant. It should be acknowledged that such insignificant result translates to significant findings (“How science goes wrong” 19-25). This is because either such research with similar molecules will not be appreciated, thus saving time, money and utilization of resources. Finally, the pressure of publish or perish concept should be discouraged and grants must be allocated for viable research without any time-bound limitations (“Trouble at the lab’ 19-25).
Works Cited
“How science goes wrong”. The Economist Intelligence Unit N.A., Incorporated, London,
2013:19-25. Print
 Huff, Darrell. “How to Lie with Statistics”. London: Penguin Books, 1991.Print
“Trouble at the lab; Unreliable research”. The Economist Intelligence Unit N.A.,
Incorporated, London, 2013.19-25. Print