DATA FROM OTHERS

Data collected by others can be premises.

One of the criteria for scientific rigor in data collection is that methods be reliable (making the same measurement of the same phenomenon yields the same result; Carmines and Zeller, 1979). For reliable measurements, who collects the data does not change the data themselves. Therefore, data rigorously collected by other researchers can also be used as premises for reasoned arguments. For example:

PREMISE: Our measurements of sprinting speed supports the hypothesis that caffeine increases sprint performance.

PREMISE: Moderate doses of caffeine can also increase performance during endurance tasks (Southward et al., 2018).

CONCLUSION: Therefore, data from sprint and endurance performance both support the general hypothesis that moderate doses of caffeine increase motor performance.

The second premise in the argument references a conclusion reasonably derived from data published in a previous study (Southward et al., 2018).

Published scientific studies differ in quality and the strength of their conclusions (Ebell et al., 2004). Researchers invest years in training and work experience to be able to critically evaluate the quality of scientific publications. However, some basic criteria for determining whether a published study is acceptable for supporting a premise are

1) Your premise accurately reflects the data or conclusions of the study.

2) The study you cite is quantitative (not qualitative, testimonial, editorial, etc.).

3) The publication you cite has undergone a rigorous peer-review process.

Scientific publications do NOT commonly include direct quotes from other papers. Because you are constructing a premise (using previously-published data) that must clearly fit into your argument, direct quotes are seldom appropriate. Instead, explain (paraphrase) the previously-measured data in a way that fits within your argument.

The type and format of citations differ among publications. Simple formats such as (Author, date) are sufficient for contexts where word limits are not a constraint.

Scientific publications use a wide variety of format, fonts, and citation styles. Different journals use a wide range of page layouts, margins, indents, and every other aspect of presenting publications. For example, whereas "APA" format may be used within psychology, APA style is not used in many other fields.

However, scientific publications do commonly use in-text citations and bibliographies at the end of papers, and do not commonly use footnotes. In-text citation styles differ among publications: some publications use (Author, date), others use numbers (e.g. in brackets: [1] or superscripts1). Bibliography format differs even more among journals, books, and online databases. Therefore, there is no standard for formatting scientific communication and references. 

In-text citations and bibliographies have one primary purpose: to allow you to find the referenced information (e.g. in the library or in an online database). Scientific communication is indexed (organized) by author name. Therefore, author name is usually an important part of finding publications. 

However, organizing information based on author name does not mean that the authors of a study themselves are particularly important.  Again, if data are valid and reliable, then it doesn't matter who collected and analyzed the data. It is the data and the conclusions from the data, not the author, that we use as a premise. Therefore, do not make authors the subject of sentences in scientific publications. Instead:

Place references to past research in parentheses at the END of sentences.

For example, do NOT write sentences such as:

"Jindrich and Full (2002) found that intrinsic muscle properties contribute to locomotor stability."

Instead, write sentences that focus on the data or conclusions of past studies, with references at the END of the sentence:

"Intrinsic muscle properties contribute to locomotor stability (Jindrich and Full, 2002)."