Towards a better framework for estimative intelligence – addressing quality through a systematic approach to uncertainty handling

Simple item page
dc.contributor.authorIsaksen, Bjorn G. M.
dc.contributor.authorMcNaught, Ken R.
dc.date.accessioned2023-06-25T12:21:49Z
dc.date.available2023-06-25T12:21:49Z
dc.date.issued2023-06-22
dc.description.abstractThe analytic standards governing the production of intelligence are outlined in a number of Intelligence Community Directives (ICDs). In this paper, we are concerned with ICDs 203, 206 and 208 and, in particular, how these relate to the handling of uncertainty in estimative intelligence. An inductive thematic analysis is employed which identifies several recurring themes. In addition, a conceptual map is developed which highlights relationships and the level of inter-connectedness between the standards. Requirements for improved operationalization of uncertainty handling are also discussed. The question of analytic feasibility is then examined in relation to the five themes extracted from the earlier analysis. The paper concludes that a new framework for uncertainty handling is required and suggests that such a framework should contain a process to assess analytic feasibility from the outset of a study.en_UK
dc.identifier.citationIsaksen BGM, McNaught KR. (2023) Towards a better framework for estimative intelligence – addressing quality through a systematic approach to uncertainty handling. Intelligence and National Security, Volume 38, Issue 7, 2023, pp. 1127-1150en_UK
dc.identifier.issn0268-4527
dc.identifier.urihttps://doi.org/10.1080/02684527.2023.2216963
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/19886
dc.language.isoenen_UK
dc.publisherTaylor and Francisen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.titleTowards a better framework for estimative intelligence – addressing quality through a systematic approach to uncertainty handlingen_UK
dc.typeArticleen_UK

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
Towards_a_better_framework_for_estimative_intelligence-2023.pdf
Size:
1.85 MB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.63 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (CDS)