planning_ai/documents/introduction.txt

This report was produced using a generative pre-trained transformer (GPT) large-language model (LLM) to produce a summary of all responses to the related policy document. This model automatically reviews every response in detail and extracts key information to inform decision making. 

The document is structured to first consolidate all information gathered from the representations to produce a single-page executive summary. This highlights areas of particular interest to consider, and the broad consensus specified by those giving the representations.

The postcode location for the member of the public or organisation who submitted a representation is used to produce a map, showing the frequency of the representations by Ward within the Greater Cambridgeshire area. Representations from outside this area are listed rather than mapped. The postcodes enable a link to the Index of Multiple Deprivation and a geodemographic (Output Area Classification) to create graphs showing how the frequency of representations varies by areas that have different socio-economic and demographic characteristics.

The document then presents a summary of information from the responses, grouped by each Theme and Policy as they appear in the Greater Cambridgeshire local plan. In this section we incorporate citations which relate with the ‘Summary Responses’ document, to increase transparency.