Block 1 - When clicking ‘Test workflow’
- Type / Role
- n8n-nodes-base.manualTrigger - manualTrigger
- Config choices
- Version 1
Spot workplace discrimination patterns with AI
Workflow preview
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Important notice
This workflow is provided as-is. Please review and test before using in production.
1. Workflow Overview
How It Works: • Scrapes company review data from Glassdoor using ScrapingBee. • Extracts demographic based ratings using AI powered...
Best for
- Market Research automation workflows
- AI Summarization automation workflows
- advanced n8n builders looking for reusable templates
Tools used
n8n-nodes-base.manualtrigger, @n8n/n8n-nodes-langchain.lmchatopenai, n8n-nodes-base.merge, n8n-nodes-base.set, n8n-nodes-base.httprequest, n8n-nodes-base.html, @n8n/n8n-nodes-langchain.informationextractor, n8n-nodes-base.code
Source and attribution
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Ludwig.
Original n8n.io source1.1 Workflow description
- Title
- Spot workplace discrimination patterns with AI
- Workflow name
- Spot workplace discrimination patterns with AI
How It Works:
• Scrapes company review data from Glassdoor using ScrapingBee. • Extracts demographic-based ratings using AI-powered text analysis. • Calculates workplace disparities with statistical measures like z-scores, effect sizes, and p-values. • Generates visualizations (scatter plots, bar charts) to highlight patterns of discrimination or bias.
Example Visualizations:
Set Up Steps:
Estimated time: ~20 minutes. • Replace ScrapingBee and OpenAI credentials with your own. • Input the company name you want to analyze (best results with large U.S.-based organizations). • Run the workflow and review the AI-generated insights and visual reports.
This workflow empowers users to identify potential workplace discrimination trends, helping advocate for greater equity and accountability.
Additional Credit: Wes Medford
For algorithms and inspiration
1.2 Logical Blocks
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
2. Block-by-Block Analysis
Block 2 - OpenAI Chat Model1
- Type / Role
- @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
- Config choices
- Version 1
Block 3 - OpenAI Chat Model2
- Type / Role
- @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
- Config choices
- Version 1
Block 4 - Merge
- Type / Role
- n8n-nodes-base.merge - merge
- Config choices
- Version 3
Block 5 - OpenAI Chat Model
- Type / Role
- @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
- Config choices
- Version 1
Block 6 - SET company_name
- Type / Role
- n8n-nodes-base.set - set
- Config choices
- Version 3.4
Block 7 - Define dictionary of demographic keys
- Type / Role
- n8n-nodes-base.set - set
- Config choices
- Version 3.4
Block 8 - ScrapingBee Search Glassdoor
- Type / Role
- n8n-nodes-base.httpRequest - httpRequest
- Config choices
- Version 4.2
Block 9 - Extract company url path
- Type / Role
- n8n-nodes-base.html - html
- Config choices
- Version 1.2
Block 10 - ScrapingBee GET company page contents
- Type / Role
- n8n-nodes-base.httpRequest - httpRequest
- Config choices
- Version 4.2
Block 11 - Extract reviews page url path
- Type / Role
- n8n-nodes-base.html - html
- Config choices
- Version 1.2
Block 12 - ScrapingBee GET Glassdoor Reviews Content
- Type / Role
- n8n-nodes-base.httpRequest - httpRequest
- Config choices
- Version 4.2
Block 13 - Extract Overall Review Summary
- Type / Role
- n8n-nodes-base.html - html
- Config choices
- Version 1.2
Block 14 - Extract Demographics Module
- Type / Role
- n8n-nodes-base.html - html
- Config choices
- Version 1.2
Block 15 - Extract overall ratings and distribution percentages
- Type / Role
- @n8n/n8n-nodes-langchain.informationExtractor - informationExtractor
- Config choices
- Version 1
Block 16 - Extract demographic distributions
- Type / Role
- @n8n/n8n-nodes-langchain.informationExtractor - informationExtractor
- Config choices
- Version 1
Block 17 - Define contributions to variance
- Type / Role
- n8n-nodes-base.set - set
- Config choices
- Version 3.4
Block 18 - Set variance and std_dev
- Type / Role
- n8n-nodes-base.set - set
- Config choices
- Version 3.4
Block 19 - Calculate P-Scores
- Type / Role
- n8n-nodes-base.code - code
- Config choices
- Version 2
Block 20 - Sort Effect Sizes
- Type / Role
- n8n-nodes-base.set - set
- Config choices
- Version 3.4
Block 21 - Calculate Z-Scores and Effect Sizes
- Type / Role
- n8n-nodes-base.set - set
- Config choices
- Version 3.4
Block 22 - Format dataset for scatterplot
- Type / Role
- n8n-nodes-base.code - code
- Config choices
- Version 2
Block 23 - Specify additional parameters for scatterplot
- Type / Role
- n8n-nodes-base.set - set
- Config choices
- Version 3.4
Block 24 - Quickchart Scatterplot
- Type / Role
- n8n-nodes-base.httpRequest - httpRequest
- Config choices
- Version 4.2
Showing the first 24 of 38 workflow blocks. Download the JSON for the full node graph.
3. Summary Table
| Workflow | Spot workplace discrimination patterns with AI |
|---|---|
| Complexity | advanced |
| Nodes | 38 |
| Categories | Market Research, AI Summarization |
| Author | Ludwig |
| Published | 30 Jan 2025 |
4. Reproducing the Workflow from Scratch
-
1. Download the workflow JSON
Use the JSON export at /data/workflows/2825/2825.json as the source template for this automation.
-
2. Import the template into n8n
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
-
3. Configure credentials and variables
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
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4. Test with sample data
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
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5. Activate and monitor
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
5. General Notes & Resources
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
Frequently asked questions
What does Spot workplace discrimination patterns with AI do?
How It Works: • Scrapes company review data from Glassdoor using ScrapingBee. • Extracts demographic based ratings using AI powered...
What do I need before importing this workflow?
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Can I customize this workflow?
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Market Research, AI Summarization use case.