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Data cooking

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Data Cooking,
Data falsification,
Data Fabrication

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Data cooking

  1. 1. DATA COOKING: AN OVERVIEW Presented By: SHIKHA AWASTHI Junior Research Fellow Department of Library & Information Science Baba Saheb Bheem Rao Ambedkar University Lucknow, 226025
  2. 2. RESEARCH IS WHAT I’M DOING WHEN I DON’T KNOW WHAT I AM DOING. WERNHER VON BRAUN As researchers who often work with qualitative data, we frequently asked to review qualitative papers and to speak about how to conduct qualitative research. Through these experiences, we have come to believe that there are prevalent misconceptions about the range of roles that qualitative data can play in research on strategic organization.
  3. 3. CONTD… This is an overview of data cooking which means the centrality of the relationship between analytic perspectives and methodological issues and the consequent requirement to go beyond purely a ‘cookbook’ version of research methods.
  4. 4. WHAT IS DATA COOKING  Data Cooking is falsification and fabrication of data which unfortunately is becoming the part of scientific research throughout the world. By : Haider A. Naqvi
  5. 5. EXAMPLE: The most common practice seen at times is to increase the number to meet the sample size requirement; after having done 50 or so questionnaires/interviews, the researcher increase the sample size (by just multiplying by 2, 4 even 10) because either he/she thinks that he/she does not need to or he/ she does not have time for it.
  6. 6. CONTD…  New york Times senior reporter Jayson Blair forced to resign after being accused of doing fraud with the data. The newspaper said at least 36 of the 73 articles he had written had problems with accuracy calling and deception a “low point” in the news paper’s history.
  7. 7. RELATED TERMS  Data falsification,  Data fabrication,  Cherry-picking,  Data rigging used for data manipulation which means the data itself might be correct, but the picking of certain data points and twisting that data to make it look like it means something different in order to support your hypothesis is unethical.
  8. 8. BUT WHY IT HAPPENS Lacking training research methods, additional burden of meeting deadlines for promotions, people resort to tinkering with numbers. Another compulsion behind this falsification is that negative results are not interesting to publishers.
  9. 9. PREVENTING DATA COOKING  We are in need of developing a system which deters such academic misconduct;  Keep portfolios of student writing  Vary assignments and topic suggestions each semester  Describe the degree of collaboration is acceptable to your students  training people in research integrity through mentorship from the grounding years,  supervising and auditing the high-stake projects and penalizing those who are found guilty.
  10. 10. CONTD…  Require an annotated bibliography  Shorter papers are okay  Academic leadership has to work hand-in-hand with researchers and journal editors to root out the evil of this research misconduct.

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