Statistical frameworks
Frameworks are a well recognised tool used to support statistical measurement, data analysis and analytical commentary. A primary function of a framework is to 'map' the conceptual terrain surrounding an area of interest. In other words, frameworks can define the scope of inquiry, delineate the important concepts associated with a topic, and organise these into a logical structure. As in the matrix above, each element identified in a statistical framework can represent a specific area about which data is needed. Frameworks can thus be used to direct investigation, or to assess the coverage of statistical programs.
The elements included within a framework can vary widely in nature, depending on the topic of interest. Frameworks may identify and differentiate important ideas (e.g. income, consumption, wealth), important population groups (e.g. employed, unemployed, not in the labour force), key entities and players (e.g. people, organisations), or other prominent factors such as resources, environmental factors, or barriers to participation, to name a few. Frameworks often identify counting units of interest for a particular topic (some common counting units are described below).
Frameworks can also show the key relationships, processes or flows that exist between elements. For example, some elements identified in a framework may impact upon others (e.g. resources, lifestyle factors and interventions may all affect the health status of an individual). In some instances flows from one state to another are of interest (e.g. from needing education, through educational activity, to acquiring an educational qualification and gaining suitable employment). In such frameworks, barriers to progression through an ideal flow may be of interest.
Ultimately, the content and form a framework takes will be determined by the nature and scope of the topic, the purpose of the framework, and the perspective of those designing it. In general, successful frameworks share some common attributes, such as being:
- comprehensive but concise;
- dynamic and flexible to allow for change; and
- cognisant of other frameworks, classifications and standards.
Above all, frameworks represent an agreed way of thinking about an area of interest, and are therefore valuable in promoting standards, consistency and comparability across data collections and between jurisdictions (e.g. states and countries) and sectors (e.g. public and private).
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