Using Sensemaking Technique to Construct Scientific Explanations in Organizational Research

Everest Turyahikayo

doi:doi:10.11648/j.ijp.20190704.15

| Peer-Reviewed

Using Sensemaking Technique to Construct Scientific Explanations in Organizational Research

Everest Turyahikayo

Published in International Journal of Philosophy (Volume 7, Issue 4)

Received: 3 October 2019 Accepted: 26 October 2019 Published: 12 December 2019

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

In the philosophy of science, an impression is created that scientific explanations are perhaps a preserve of physical and natural sciences. Although social scientists in organizational research have borrowed most modals of scientific explanations from natural scientists, they have met harsh criticism from their counterparts in the natural and physical sciences. This paper set out to explain how scientific explanations can be constructed successfully in organizational studies using modals borrowed from natural sciences. Basing on the critical literature review, the paper has successfully argued that, organizational research applies models of scientific explanations using sense making. In the case of the covering law model, it has been argued that the model connects well with sense making in organizational research in many respects since sense making recognizes explanandum in terms of organizational events that people experience in everyday life. The paper has also indicated that in the statistical-probabilistic model explanations are based on non-deductive reasoning and make it hard for the researcher to predict the explanandum with certainty except with some degree of probability. This applies in both organizational studies as well as in natural sciences. Like in the statistical probability model, causal-effect relationships can also be demonstrated statistically in organizational research. Moreover, the fact that organizational researchers have different traditions from those of ‘number crunchers’ does not make such traditions inferior. Lastly, the unification model portrays scientific explanations as constructed in a unified design. The paper has shown that in organizational research, unification manifests quite differently from the natural sciences. Organizations operate in unstable condition in the sense that there are so many disciplines under organizational research.

Published in	International Journal of Philosophy (Volume 7, Issue 4)
DOI	10.11648/j.ijp.20190704.15
Page(s)	167-172
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Philosophy, Scientific Explanation, Sense Making, Organizational Research

References

[1]	M. Friedman, “Explanation and Scientific Understanding,” J. Philos., vol. 71, no. 1, p. 5, 2006.
[2]	M. Braaten and M. Windschitl, “Working toward a stronger conceptualization of scientific explanation for science education,” Sci. Educ., vol. 95, no. 4, pp. 639–669, 2011.
[3]	J.-X. Yao, Y.-Y. Guo, and K. Neumann, “Towards a hypothetical learning progression of scientific explanation,” Asia-Pacific Sci. Educ., vol. 2, no. 1, 2016.
[4]	C. C. Hsu, C. H. Chiu, C. H. Lin, and T. I. Wang, “Enhancing skill in constructing scientific explanations using a structured argumentation scaffold in scientific inquiry,” Comput. Educ., vol. 91, pp. 46–59, 2015.
[5]	J. H. M. Wagemans, “Argumentative Patterns for Justifying Scientific Explanations,” Argumentation, vol. 30, no. 1, pp. 97–108, 2016.
[6]	W. C. Salmon, “Scientific Explanation: Three Basic Conceptions Wesley C. Salmon PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association, Vol. 1984, Volume Two: Symposia and Invited Papers. (1984), pp. 293-305.,” Philos. Sci., vol. 1984, pp. 293–305, 1984.
[7]	L. K. Berland and B. J. Reiser, “Making sense of argumentation and explanation,” Sci. Educ., vol. 93, no. 1, pp. 26–55, 2009.
[8]	A. M. Novak and D. F. Treagust, “Adjusting claims as new evidence emerges: Do students incorporate new evidence into their scientific explanations?” J. Res. Sci. Teach., vol. 55, no. 4, pp. 526–549, 2018.
[9]	F. Allard-poesi and F. Allard-poesi, “The Paradox of Sensemaking in Organizational Analysis To cite this version: HAL Id: hal-01251211 The Paradox of Sensemaking in Organizational Analysis,” vol. 12, no. 2, pp. 169–196, 2016.
[10]	P. Zhang, D. Soergel, J. L. Klavans, and D. W. Oard, “Extending sense-making models with ideas from cognition and learning theories,” Proc. Am. Soc. Inf. Sci. Technol., vol. 45, no. 1, pp. 23–23, 2009.
[11]	K. E. Weick, K. M. Sutcliffe, and D. Obstfeld, “Organizing and the Process of Sensemaking,” Organ. Sci., vol. 16, no. 4, pp. 409–421, 2005.
[12]	M. de L. Borges and C. R. Gonçalo, “Learning process promoted by sensemaking and trust: a study related to unexpected events,” Cad. EBAPE. BR, vol. 8, no. 2, pp. 260–277, 2010.
[13]	N. K. Agarwal, “Making sense of sense-making: tracing the history and development of Dervin’s Sense-Making Methodology,” Int. Perspect. Hist. Inf. Sci. Technol. Proc. ASIS & T 2012 Pre-Conference Hist. ASIS&T Inf. Sci. Technol., p. 13, 2012.
[14]	S. Maitlis and M. Christianson, “Sensemaking in Organizations: Taking Stock and Moving Forward,” Acad. Manag. Ann., vol. 8, no. 1, pp. 57–125, 2014.
[15]	C. G. Hempel, “Two Basic Types of Scientific Explanation / Inductive-Statistical Explanation,” Philos. Sci. Cent. Issues, pp. 9–19, 1998.
[16]	M. Strevens, “An argument against the unification account of explanation,” no. December, pp. 1–29, 1999.
[17]	H. Veatch, “Aspects of Scientific Explanation and Other Essays in the Philosophy of Science. Carl G. Hempel,” Philos. Sci., vol. 37, no. 2, pp. 312–314, 2002.
[18]	A. Bhattacherjee, Introduction to Research, Social Science Research: Principles, Methods, and Practices. 2012.
[19]	E. Miller, “Humean scientific explanation,” Philos. Stud., vol. 172, no. 5, pp. 1311–1332, 2015.
[20]	A. Potochnik, “Scienti fi c Explanation: Putting Communication First,” vol. 83, no. December, pp. 721–732, 2016.
[21]	M. Namvar, J. L. Cybulski, C. S. C. Phang, Y. S. Ee, and K. T. L. Tan, “Simplifying sensemaking: Concept, process, strengths, shortcomings, and ways forward for information systems in contemporary business environments,” Australas. J. Inf. Syst., vol. 22, 2018.
[22]	I. Jarvie, J. Zamora-Bonilla, and D. Steel, “Causality, Causal Models, and Social Mechanisms,” SAGE Handb. Philos. Soc. Sci., pp. 288–304, 2014.
[23]	L. J. Rennie, “Dealing with Problems of Causality in Impact Studies,” pp. 1–6, 2014.
[24]	P. Thagard, “Theory Evaluation,” Comput. Philos. Sci., pp. 3–23, 2018.
[25]	K. Weber and M. A. Glynn, “Making sense with institutions: Context, thought and action in Karl Weick’s theory,” Organ. Stud., vol. 27, no. 11, pp. 1639–1660, 2006.
[26]	J. Gerring, Causation: A unified framework for the social sciences, vol. 17, no. 2. 2005.
[27]	A. Sliva, S. N. Reilly, R. Casstevens, and J. Chamberlain, “Tools for Validating Causal and Predictive Claims in Social Science Models,” Procedia Manuf., vol. 3, no. Ahfe, pp. 3925–3932, 2015.
[28]	A. Gelman and M. Betancourt, “Does quantum uncertainty have a place in everyday applied statistics?” Behav. Brain Sci., vol. 36, no. 3, p. 285, 2013.
[29]	B. W. Salmon, “Scientific Explanation- Causation and Unification,” Philos. Sci., vol. 41, no. 0102458, pp. 40–41, 2005.
[30]	C. D. Green and C. D. Green, “Review of General Psychology Why Psychology Isn’ t Unified, and Probably Never Will Be Why Psychology Isn’ t Unified, and Probably Never Will Be,” vol. 19, no. 3, pp. 207–214, 2015.
[31]	T. Lynam and C. Fletcher, “Sensemaking: A complexity perspective,” Ecol. Soc., vol. 20, no. 1, 2015.
[32]	S. E. Woo, E. H. O’Boyle, and P. E. Spector, “Best practices in developing, conducting, and evaluating inductive research,” Hum. Resour. Manag. Rev., vol. 27, no. 2, pp. 255–264, 2017.
[33]	M. Coccia, “Methods of Inquiry in Social Sciences: An Introduction,” Ssrn, no. 27, 2018.
[34]	J. Woiceshyn and U. Daellenbach, “Evaluating inductive vs deductive research in management studies,” Qual. Res. Organ. Manag. An Int. J., vol. 13, no. 2, pp. 183–195, 2018.
[35]	R. J. Ormerod, “Rational inference: Deductive, inductive and probabilistic thinking,” J. Oper. Res. Soc., vol. 61, no. 8, pp. 1207–1223, 2010.
[36]	P. Lanier, “Frameworks of Causal Inference for Improving Intervention, Prediction, and Imagination in Family Violence Research: a Commentary on Rose (2018),” J. Fam. Violence, 2019.
[37]	A. Sobrino, J. A. Olivas, and C. Puente, “Causality and imperfect causality from texts: A frame for causality in social sciences.” 2010 IEEE World Congr. Comput. Intell. WCCI 2010, 2010.
[38]	S. L. Bressler and A. K. Seth, “Wiener-Granger Causality: A well established methodology,” Neuroimage, vol. 58, no. 2, pp. 323–329, 2011.
[39]	J. Persson, A. Hornborg, L. Olsson, and H. Thorén, “Toward an alternative dialogue between the social and natural sciences,” Ecol. Soc., vol. 23, no. 4, 2018.
[40]	K. Wu, P. Marijuan, and Z. Wang, “A Dialogue about the Nature and Unification of Information Science and Information Philosophy,” Proceedings, vol. 1, no. 3, p. 72, 2017.
[41]	D. J. Watts, “Should social science be more solution-oriented?” Nat. Hum. Behav. vol. 1, no. 1, 2017.
[42]	M. R. Armat, A. Assarroudi, M. Rad, H. Sharifi, and A. Heydari, “Inductive and deductive: Ambiguous labels in qualitative content analysis,” Qual. Rep., vol. 23, no. 1, pp. 219–221, 2018.
[43]	T. Azungah, “Qualitative research: deductive and inductive approaches to data analysis,” Qual. Res. J., vol. 18, no. 4, pp. 383–400, 2018.

Cite This Article

Plain Text BibTeX RIS

APA Style

Everest Turyahikayo. (2019). Using Sensemaking Technique to Construct Scientific Explanations in Organizational Research. International Journal of Philosophy, 7(4), 167-172. https://doi.org/10.11648/j.ijp.20190704.15

Copy | Download

ACS Style

Everest Turyahikayo. Using Sensemaking Technique to Construct Scientific Explanations in Organizational Research. Int. J. Philos. 2019, 7(4), 167-172. doi: 10.11648/j.ijp.20190704.15

Copy | Download

AMA Style

Everest Turyahikayo. Using Sensemaking Technique to Construct Scientific Explanations in Organizational Research. Int J Philos. 2019;7(4):167-172. doi: 10.11648/j.ijp.20190704.15

Copy | Download

@article{10.11648/j.ijp.20190704.15,
  author = {Everest Turyahikayo},
  title = {Using Sensemaking Technique to Construct Scientific Explanations in Organizational Research},
  journal = {International Journal of Philosophy},
  volume = {7},
  number = {4},
  pages = {167-172},
  doi = {10.11648/j.ijp.20190704.15},
  url = {https://doi.org/10.11648/j.ijp.20190704.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijp.20190704.15},
  abstract = {In the philosophy of science, an impression is created that scientific explanations are perhaps a preserve of physical and natural sciences. Although social scientists in organizational research have borrowed most modals of scientific explanations from natural scientists, they have met harsh criticism from their counterparts in the natural and physical sciences. This paper set out to explain how scientific explanations can be constructed successfully in organizational studies using modals borrowed from natural sciences. Basing on the critical literature review, the paper has successfully argued that, organizational research applies models of scientific explanations using sense making. In the case of the covering law model, it has been argued that the model connects well with sense making in organizational research in many respects since sense making recognizes explanandum in terms of organizational events that people experience in everyday life. The paper has also indicated that in the statistical-probabilistic model explanations are based on non-deductive reasoning and make it hard for the researcher to predict the explanandum with certainty except with some degree of probability. This applies in both organizational studies as well as in natural sciences. Like in the statistical probability model, causal-effect relationships can also be demonstrated statistically in organizational research. Moreover, the fact that organizational researchers have different traditions from those of ‘number crunchers’ does not make such traditions inferior. Lastly, the unification model portrays scientific explanations as constructed in a unified design. The paper has shown that in organizational research, unification manifests quite differently from the natural sciences. Organizations operate in unstable condition in the sense that there are so many disciplines under organizational research.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Using Sensemaking Technique to Construct Scientific Explanations in Organizational Research
AU  - Everest Turyahikayo
Y1  - 2019/12/12
PY  - 2019
N1  - https://doi.org/10.11648/j.ijp.20190704.15
DO  - 10.11648/j.ijp.20190704.15
T2  - International Journal of Philosophy
JF  - International Journal of Philosophy
JO  - International Journal of Philosophy
SP  - 167
EP  - 172
PB  - Science Publishing Group
SN  - 2330-7455
UR  - https://doi.org/10.11648/j.ijp.20190704.15
AB  - In the philosophy of science, an impression is created that scientific explanations are perhaps a preserve of physical and natural sciences. Although social scientists in organizational research have borrowed most modals of scientific explanations from natural scientists, they have met harsh criticism from their counterparts in the natural and physical sciences. This paper set out to explain how scientific explanations can be constructed successfully in organizational studies using modals borrowed from natural sciences. Basing on the critical literature review, the paper has successfully argued that, organizational research applies models of scientific explanations using sense making. In the case of the covering law model, it has been argued that the model connects well with sense making in organizational research in many respects since sense making recognizes explanandum in terms of organizational events that people experience in everyday life. The paper has also indicated that in the statistical-probabilistic model explanations are based on non-deductive reasoning and make it hard for the researcher to predict the explanandum with certainty except with some degree of probability. This applies in both organizational studies as well as in natural sciences. Like in the statistical probability model, causal-effect relationships can also be demonstrated statistically in organizational research. Moreover, the fact that organizational researchers have different traditions from those of ‘number crunchers’ does not make such traditions inferior. Lastly, the unification model portrays scientific explanations as constructed in a unified design. The paper has shown that in organizational research, unification manifests quite differently from the natural sciences. Organizations operate in unstable condition in the sense that there are so many disciplines under organizational research.
VL  - 7
IS  - 4
ER  -

Copy | Download

Author Information

Everest Turyahikayo

Department of Public Administration and Management, Uganda Management Institute, Kampala, Uganda

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Everest Turyahikayo. (2019). Using Sensemaking Technique to Construct Scientific Explanations in Organizational Research. International Journal of Philosophy, 7(4), 167-172. https://doi.org/10.11648/j.ijp.20190704.15

Copy | Download

ACS Style

Everest Turyahikayo. Using Sensemaking Technique to Construct Scientific Explanations in Organizational Research. Int. J. Philos. 2019, 7(4), 167-172. doi: 10.11648/j.ijp.20190704.15

Copy | Download

AMA Style

Everest Turyahikayo. Using Sensemaking Technique to Construct Scientific Explanations in Organizational Research. Int J Philos. 2019;7(4):167-172. doi: 10.11648/j.ijp.20190704.15

Copy | Download

@article{10.11648/j.ijp.20190704.15,
  author = {Everest Turyahikayo},
  title = {Using Sensemaking Technique to Construct Scientific Explanations in Organizational Research},
  journal = {International Journal of Philosophy},
  volume = {7},
  number = {4},
  pages = {167-172},
  doi = {10.11648/j.ijp.20190704.15},
  url = {https://doi.org/10.11648/j.ijp.20190704.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijp.20190704.15},
  abstract = {In the philosophy of science, an impression is created that scientific explanations are perhaps a preserve of physical and natural sciences. Although social scientists in organizational research have borrowed most modals of scientific explanations from natural scientists, they have met harsh criticism from their counterparts in the natural and physical sciences. This paper set out to explain how scientific explanations can be constructed successfully in organizational studies using modals borrowed from natural sciences. Basing on the critical literature review, the paper has successfully argued that, organizational research applies models of scientific explanations using sense making. In the case of the covering law model, it has been argued that the model connects well with sense making in organizational research in many respects since sense making recognizes explanandum in terms of organizational events that people experience in everyday life. The paper has also indicated that in the statistical-probabilistic model explanations are based on non-deductive reasoning and make it hard for the researcher to predict the explanandum with certainty except with some degree of probability. This applies in both organizational studies as well as in natural sciences. Like in the statistical probability model, causal-effect relationships can also be demonstrated statistically in organizational research. Moreover, the fact that organizational researchers have different traditions from those of ‘number crunchers’ does not make such traditions inferior. Lastly, the unification model portrays scientific explanations as constructed in a unified design. The paper has shown that in organizational research, unification manifests quite differently from the natural sciences. Organizations operate in unstable condition in the sense that there are so many disciplines under organizational research.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - Using Sensemaking Technique to Construct Scientific Explanations in Organizational Research
AU  - Everest Turyahikayo
Y1  - 2019/12/12
PY  - 2019
N1  - https://doi.org/10.11648/j.ijp.20190704.15
DO  - 10.11648/j.ijp.20190704.15
T2  - International Journal of Philosophy
JF  - International Journal of Philosophy
JO  - International Journal of Philosophy
SP  - 167
EP  - 172
PB  - Science Publishing Group
SN  - 2330-7455
UR  - https://doi.org/10.11648/j.ijp.20190704.15
AB  - In the philosophy of science, an impression is created that scientific explanations are perhaps a preserve of physical and natural sciences. Although social scientists in organizational research have borrowed most modals of scientific explanations from natural scientists, they have met harsh criticism from their counterparts in the natural and physical sciences. This paper set out to explain how scientific explanations can be constructed successfully in organizational studies using modals borrowed from natural sciences. Basing on the critical literature review, the paper has successfully argued that, organizational research applies models of scientific explanations using sense making. In the case of the covering law model, it has been argued that the model connects well with sense making in organizational research in many respects since sense making recognizes explanandum in terms of organizational events that people experience in everyday life. The paper has also indicated that in the statistical-probabilistic model explanations are based on non-deductive reasoning and make it hard for the researcher to predict the explanandum with certainty except with some degree of probability. This applies in both organizational studies as well as in natural sciences. Like in the statistical probability model, causal-effect relationships can also be demonstrated statistically in organizational research. Moreover, the fact that organizational researchers have different traditions from those of ‘number crunchers’ does not make such traditions inferior. Lastly, the unification model portrays scientific explanations as constructed in a unified design. The paper has shown that in organizational research, unification manifests quite differently from the natural sciences. Organizations operate in unstable condition in the sense that there are so many disciplines under organizational research.
VL  - 7
IS  - 4
ER  -

Copy | Download