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Chapter 6

🧽 Story cleaning

✅ Once you have collected all the stories, double-check that all information is complete and that you have received informed consent from all storytellers. Log all information in a spreadsheet including story title, link to story, storyteller name or code, and whether informed consent was obtained and where it is documented.

Note: If your project has gone through the full research ethical clearance process and your project is expected to adhere to guidance around protecting people’s information, you might need to anonymize some data that you collect. The people whose stories you collect should be made fully aware how their information and stories will be recorded, stored, analyzed and used, including personally identifiable information. This should be outlined in your protocol.

🚧 Based on your defined topic, community, and expected areas of change, review all stories and screen out any stories that do not meet the criteria. It is important that you consider how to avoid bias in this step, such as having multiple team members screen stories and double-check one another’s work.

🤖 If needed, convert stories into text-based formats that allow for easier analysis in three ways:

  1. AI-assisted transcription of audio
  2. AI-assisted closed captioning of video
  3. AI-assisted handwriting/text recognition software

You can also use the more reliable but labor-intensive method of human transcription. However, if you do rely on AI tools, have a human check all text outputs against the originals to ensure accuracy.

🧹 De-identify stories by removing identifiable storyteller information, such as names and locations. This will allow for the story analysts to focus on universal themes and experiences rather than particulars.

🌐Check with your community expert on specific cultural references and slang, and where appropriate, provide definitions of these to aid understanding in analysis and interpretation. 

📝If needed, verify the stories with the storyteller to ensure you have captured their points accurately, especially if there is something missing or meaning is lost due to a transcription or other translation error

Randomize and divide stories equally to assign to focus group participants (we suggest assigning no more than 2-3 stories per person). Stories should be randomly assigned in equal numbers among focus groups. The number of stories to be analyzed per focus group should ideally not exceed 20 stories, or it will be difficult to get through discussing all the stories. These stories will be read by participants before the focus group is convened.

Visit the resources page for templates, tools, and more.
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