Foundational for Professionalism

The site logo was designed collaboratively by Valerie Nirala, David Liebke, and Rochelle Tractenberg.

The logo is an abstract version of this 2013 model:

Model of the critical role for ethical reasoning in developing and supporting professionalism in statistics (and data science) (Tractenberg, 2013; adapted from Arnold & Stern 2006, Figure B.). Knowledge and communication skills, when combined with ethical reasoning, are shown to be the foundation of transparency, precision, accuracy, accountability, and logical and scientific justification of competent statistical work, the pillars that support professionalism in statistical practices (among other disciplines). A critical feature of this adaptation is how ethical reasoning – not “ethics”, not “responsible conduct of research”, or other ambiguous constructs – is treated as foundational for professionalism in statistics and data science, but in turn, communication and knowledge are foundational for ethical reasoning.
Figure 1: Model of professionalism specific to quantitative sciences. (from Tractenberg, 2013). The model is the basis for the site logo.

The elements of the logo are as follows:

In a 2013 paper in the Proceedings of the Joint Statistics Meetings, I created a figure of the foundations of “professionalism” for statistical practices (including statistics, data science, biostatistics). However, the original figure (Arnold & Stern 2006) was for medicine; thus the more abstract version of the figure (the logo) suggests that the pillars represent whatever is specific to the discipline. Five key elements of competent work by statisticians/in statistical practice were described by Rosnow & Rosenthal (2011):

  • transparency,
  • precision,
  • accuracy,
  • accountability, and
  • logical and scientific justification <for work>.

These five elements comprising competent statistical practices are the columns in the revised logo figure. However, in addition to the two foundational elements of Arnold and Stern (Knowledge, Communication), Ethical Reasoning is also in the foundation (plinth), to complete the logo. Together, these five pillars and 3 foundational elements “support” the argument that professionalism (the roof/top triangle) is built upon a foundation with the key plinth contributions as well as the specific disciplinary pillars. These elements are relevant for any scientific field, and it is also true that ethical reasoning can support these elements in individual practice (e.g., Tractenberg 2022-a) and when facing ethical challenges that can arise when practicing with/for others (e.g., Tractenberg 2022-b).

Thoughtful attention to formal integration of ethical reasoning into instruction (e.g., throughout a degree program) can help learners develop “…the sense of being a professional…the use of professional judgment and reasoning … critical self evaluation and self-directed learning…” (Paterson et al. 2002:7) The Ethical Guidelines for Statistical Practice (ASA, 2022) were revised (2016/2018/2022) to specifically support professionalism, viz “…the skill, good judgment, and polite behavior that is expected from a person who is trained to do a job well.” ASA members and nonmembers alike must promote understanding, through trust in their professionalism and judgment, when they engage in statistical practices and data science. These revisions also include – should be followed by – all those who engage in statistical practice, where ” “statistical practice” includes activities such as: designing the collection of, summarizing, processing, analyzing, interpreting, or presenting, data; as well as model or algorithm development and deployment.” Moreover, “the term “statistical practitioner” includes all those who engage in statistical practice, regardless of job title, profession, level, or field of degree.” (ASA 2022)

“…(E)thics is not a vaccine that can be administered in one dose and have long lasting effects no matter how often, or in what conditions, the subject is exposed to the disease agent”. (National Academy of Engineering, 2009:34).

The logo reflects a model of professionalism specific to quantitative sciences, with ethical reasoning as integral for both effective work (e.g., Rosnow & Rosenthal, 2011) and the development of a sense of professionalism (e.g., Arnold & Stern, 2006). The American Statistical Association (ASA) Ethical Guidelines for Statistical Practice (2022) and the Association for Computing Machinery (ACM) Code of Ethics (2018) implicitly blend ethics and professionalism. Both of these ethical practice standards are also explicit in their applicability to any person, irrespective of job title or educational background, that will utilize the tools, methods, and constructs of these professions.

References

  • Arnold L & Stern DT. (2006).  A framework for measuring professionalism. In DT Stern (Ed.), Measuring Medical Professionalism. New York, NY: Oxford University Press. Pp. 3-14.
  • American Statistical Association (ASA) ASA Ethical Guidelines for Statistical Practice-revised (2022) downloaded from https://www.amstat.org/ASA/Your-Career/Ethical-Guidelines-for-Statistical-Practice.aspx on 1 January 2022.
  • Association for Computing Machinery (ACM). Code of Ethics (2018) downloaded from https://www.acm.org/about-acm/code-of-ethics on 12 October 2018.
  • Grace S & Trede F. (2011). Developing professionalism in physiotherapy and dietetics students in professional entry courses.  Studies in Higher Education.DOI: 10.1080/03075079.2011.603410.
  • National Academy of Engineering and National Research Council. (2009). Ethics Education and Scientific and Engineering Research: What’s Been Learned? What Should Be Done?. Washington, DC: The National Academies Press.
  • Paterson, M., J. Higgs, S. Wilcox, and M. Villenuve. 2002. Clinical reasoning and self-directed1earning: Key dimensions in professional education and professional socialisation. Focus on Health Professional Education 4, no. 2: 5–21.
  • Rosnow RL & Rosenthal R. (2011). Ethical principles in data analysis: An overview. In AT Panter & SK Sterba (Eds.), Handbook of Ethics in Quantitative Methodology. New York, NY: Taylor and Francis. Pp. 37-59.
  • Tractenberg, RE. (2015). Professionalism, professional identity, and ethics education in statistics: Discussion. Presentation at the 2015 Joint Statistical Meetings, Seattle, WA.
  • Tractenberg RE, Russell A, Morgan G, et al. (2014).  Amplifying the reach and resonance of ethical codes of conduct through ethical reasoning: preparation of Big Data users for professional practice. Science and Engineering Ethics. http://link.springer.com/article/10.1007%2Fs11948-014-9613-1 PMID: 25431219
  • Tractenberg RE. (2013). Ethical Reasoning for Quantitative Scientists: A Mastery Rubric for Developmental Trajectories, Professional Identity, and Portfolios that Document Both. Proceedings of the 2013 Joint Statistical Meetings, Montreal, Quebec, Canada.  Pp. 3959-3973.
  • Trede F. (2012).  Role of work-integrated learning in developing professionalism and professional identity. Asia-Pacific Journal of Cooperative Education 13(3): 159-67.
  • Trede F, Macklin R & Bridges D. (2011).  Professional Identity development: a review of the higher education literature. Studies in Higher Education 37(3): 365-384.

rochelle tractenberg