what are your thoughts after reading the following articles?

Question

Interesting articles about the way we have been learning and teaching science

if you are interested read one or both articles and let us know what you think!

Silence is Never Neutral; Neither is Science

The Intersection of Science and Racism

Answer 1

Instead of giving an answer, I want to help you think.

Whenever you are asked to read an article for a class assignment, try to actively annotate it. As you read the article, what thoughts come into your head? What past experiences have you had that relate to the article? Have you found supporting or conflicting evidence? What overall conclusion can you draw from each paragraph as well as the article as a whole?

When you read these 2 articles, take notes. This will help you share your thoughts for the assignment.

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Here is some of my subjective input (with some evidence):

Silence Is Never Neutral; Neither Is Science: From the title itself, what do you think the author will talk about? Silence is never neutral: what does this mean? Can you think of a time where being silent has shown someone's opinion? For example, have you ever witnessed someone being bullied and you didn't intervene? Perhaps you were fearful of being bullied yourself; bottom line, you did not speak up and were a bystander. In today's world, there is an extreme political divide. Can you think of any examples where a group of people did not speak up, and therefore showed support to one side?

And the second part, 'Neither is Science' or Science is Never Neutral: what does this mean? How can science not be neutral? Whenever you read scientific literature, have you ever noticed a section called 'conflicts of interest'? In some cases, scientific research can be biased; sometimes data can be 'cherry picked' to show an effect that was not initially there in all of the data points. If a scientist publishes significant work, they can attain greater recognition. The integrity of science is lost; here, data that did not support their hypothesis was excluded. Also, a company funding a project may want exceptional results to bring a new drug to the market for profit. Another example can be seen in a recent Netflix documentary called Coded Bias (https://www.netflix.com/title/81328723). An algorithm used to detect facial features was trained on a dataset of predominantly white individuals. How do you think this bias impacts the algorithm when analyzing minority populations?

The example mentioned previously also links with 'The Intersection of Science and Racism". In science, there is a lack of minority representation in clinical trials and datasets. Additionally, racism is still found in the workplace; quickly google statistics of minorities (especially black individuals) in science PhD programs or the number of papers published by minorities compared to white individuals. The article itself contains many helpful links to view the wide scope of discrimination in many aspects of science.

Lastly, I am of European decent. My perspective is still biased; I have experienced sexism in science, but I am not qualified to speak for minority voices. Read articles, listen to podcasts, and watch videos of individuals who have experienced racism (in general and in science) to attain a better understanding. Remember, 'Silence is Never Neutral'. Will you remain silent if you witness racism?