Skip to main content Accessibility help
×
Hostname: page-component-5c6d5d7d68-7tdvq Total loading time: 0 Render date: 2024-08-18T01:33:44.256Z Has data issue: false hasContentIssue false

8 - Retrospect and Prospect

from Part IV - What Is to Be Done?

Published online by Cambridge University Press:  05 March 2014

Fred L. Bookstein
Affiliation:
University of Washington and Universität Wien, Austria
Get access

Summary

This last chapter summarizes the implications of all that has preceded for the praxis of statistical science in the near future. It is divided into three sections. Section 8.1 introduces one final example: another study of fetal alcohol exposure, this time based on ultrasound brain images of infants. With its aid I review the notions of abduction and consilience from a point of view emphasizing the psychosocial structures of science rather than the logic of these forms of inference per se. If a scientific fact is “a socially imposed constraint on speculative thought” (Ludwik Fleck's main theme), then abduction and consilience work in somewhat contrasting ways to effect that constraint depending on whether the scientific context is one of simple measurement or the probing of a complex system. Section 8.2 shows how all these procedures depend on prior consensus as to what constitutes agreement or disagreement between a numerical representation of some pattern and an expectation about a scientific regularity. In the final section I step back to examine the whole protocol by which forms of numerical reasoning are communicated across the academic and technological generations. The chapter concludes with some recommendations for major changes in the way we teach statistics. If this praxis of abduction cum consilience toward the understanding of complex systems is to keep up with the requirements for science and for the public understanding of science over the next few decades, special attention must be paid to the curricula by which all these strategies are taught to the next generation of our colleagues.

Type
Chapter
Information
Measuring and Reasoning
Numerical Inference in the Sciences
, pp. 481 - 500
Publisher: Cambridge University Press
Print publication year: 2014

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×