All Knowledge is Still Knowledge

One of the significant issues I have observed and heard of in academia is the “falsification and fabrication pandemic”, which I quote from one of the videos I saw on Instagram (suhthescholar, 2024). I found it fitting to talk about it, adding on a recent personal experience of mine.

This semester, we had a practical paper on research, and we (in groups) were expected to conduct a quantitative study. We were taken through the process of RoL, identifying variables and instruments, the statistics, writing a proposal, and so on. We conducted our survey, cleaned and scored our data, and as part of our final submission, we are to draft the analysis and discussion of the results.

As we ran our stats, the analysis did not support our hypotheses. To quote a remark by fellow team members, “How are we going to write about this?” and “I don’t think we can use this data.”

These remarks were followed by suggestions to manipulate the data to receive positive results for [only] the purpose of the submission.

Firstly, to be clear, I did not allow them to do so, and we reported the negative results with low significance. This information has no implication or applicability; it is still a reasonable finding and knowledge.

An article reported that “there were likely high proportions of falsified or plagiarised papers in neuroscience and medicine (34% and 24%, respectively), as of 2020” (Buntz, 2023). Another finding indicates that “2% of scientists admit to having falsified research at least once, and up to 34% admit other questionable research practices” (Fanelli, 2009).

I believe this stems from the academicians’ obsession with positive results, which, in turn, is a product of capitalism—going back to the Greeks, who created and transferred knowledge for the basis of understanding. However, on the other hand, the Romans believed in making and understanding knowledge only to apply it to some use—both valid and acceptable beliefs and perspectives, but only when one does not limit the other.

Leading causes of data fabrication include pressure to publish, career advancement, inadequate oversight, weak peer control, institutional failures, etc. (DuBois et al., 2013; George, 2015). In the pharmaceutical industry, researcher A studies the interaction between a chemical substrate and an active site for disease treatment. After encountering negative results, A faces pressure from the CEO, leading to adverse actions against A’s team regarding funding and resources. This tempts A to fabricate data to please stakeholders, ultimately jeopardising customer safety.

The negative findings of A could have been used to see from this standpoint: what went wrong? Why is it that there was no relationship/effect? What could be done better/alternatively? What to not do again? After all, all knowledge is still knowledge. With a shift in the mindset of the stakeholders and researchers involved, we can advance research and ensure that the advancement is ethically and morally correct. In the case of the example, instead of writing a falsified positive, they could write about why it did not work out, explain, and check if the substrate is interacting with any other entity to bring out a suitable outcome. If none, this could be a testament for future researchers to avoid repeating the same or creating better adaptations.

I recently discussed this matter with a peer, Nisha Karandikar . We had an assignment to find Q1- and Q2-rated Indian journals and write about them for an academic writing paper. Finding journals of that quartile was increasingly complex, and one of the reasons could be that the documents we published might have been subject to fabrication and that the quality of the work could have been better. Nisha said, and I quote as it stood out to me, “publishing of false data leads to poor quality of research published as a country.”. Universities in India have focused more on rote learning than experiential learning, encouraging learners towards research. State universities stand as a testament to this assumption. Research and teaching go hand in hand. To quote the economics Nobel Prize Laurent, Claudia Goldin stated, “Teaching and research are one.” In the recent stage of India, when the UGC is giving more focus to research, all of a sudden, the universities are putting pressure on the academicians to publish. The pressure to publish and the lack of interest in publishing either might decrease the quality of the research or increase the chances of falsification and fabrication.

With perspectives of purely academic research, we do a lot of intensive literature review to draw our hypotheses (for quantitative) and research questions (for qualitative). When we read supporting literature, we tend to expect positive results, though ethically, we are not supposed to conclude; we are biased beings, after all. We must reject our hypothesis when the results are negative; it can be pretty upsetting. Instead of fabricating our data, we can muster up the courage as ethical researchers and academicians, inform our readers and the academic community about our negative results, and, if possible, explain why the findings are as obtained.

Talking about the disparity between the previous literature and the results we received, possible explanations could be that the sample that we collected data from had their differences, which were significant in number, and that the time possibly was not right when the collection was done, and hence opening up the possibility for future studies to bridge these gaps, to perhaps satisfactory findings. Again, many opportunities and options are more ethical and beneficial to the community than fabricating the data.

References

Buntz, B. (2023, May 17). Data integrity scandals in biomedical research: Here’s a timeline. Drug Discovery and Development. https://www.drugdiscoverytrends.com/biomedical-research-integrity-scandals/

DuBois, J. M., Anderson, E. E., Chibnall, J., Carroll, K., Gibb, T., Ogbuka, C., & Rubbelke, T. (2013). Understanding research misconduct: A comparative analysis of 120 cases of professional wrongdoing. Accountability in Research, 20(5-6), 320–338. https://doi.org/10.1080/08989621.2013.822248

Fanelli, D. (2009). How many scientists fabricate and falsify research? A systematic review and meta-analysis of survey data. PLoS ONE, 4(5), e5738. https://doi.org/10.1371/journal.pone.0005738

George, S. L. (2015). Research misconduct and data fraud in clinical trials: Prevalence and causal factors. International Journal of Clinical Oncology, 21(1), 15–21. https://doi.org/10.1007/s10147-015-0887-3

Marques, T., Reis, N., & Gomes, J. (2019). A bibliometric study on academic dishonesty research. Journal of Academic Ethics, 17(2), 169–191. https://doi.org/10.1007/s10805-019-09328-2

suhthescholar. (2024, October 25). @suhthescholar on Instagram: “shaking the table today.” Instagram. https://www.instagram.com/reel/DBhGoJzpTC0/?utm_source=ig_web_copy_link&igsh=MzRlODBiNWFlZA==?