# EEOC Enforcement & Litigation Newsroom Scraper (`jungle_synthesizer/eeoc-enforcement-litigation-newsroom-scraper`) Actor Scrapes EEOC enforcement press releases. Extracts employer name, settlement amounts, discrimination type, statute cited (ADA/Title VII/ADEA), district office, and case numbers — turning EEOC newsroom into structured employment-risk records. - **URL**: https://apify.com/jungle\_synthesizer/eeoc-enforcement-litigation-newsroom-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Business, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## EEOC Enforcement & Litigation Newsroom Scraper Extract structured enforcement and litigation data from the [EEOC Virtual Newsroom](https://www.eeoc.gov/newsroom/search). Every press release is parsed into a machine-readable record: employer name, settlement dollar amount, discrimination type, statute cited, district office, and civil action case number. ### What you get | Field | Description | |---|---| | `title` | Full press release headline | | `url` | Canonical URL | | `date` | Publication date | | `press_release_type` | Press Release / Litigation / Settlement | | `district_office` | EEOC field or district office (e.g. "Chicago District Office") | | `respondent_employer` | Company named in the action (extracted from title) | | `settlement_amount_usd` | Settlement dollar figure as a number (null if not a settlement) | | `discrimination_type` | Array: disability, sex, pregnancy, age, race, religion, retaliation | | `statute_cited` | Array: ADA, Title VII, ADEA, GINA, EPA, PWFA | | `case_number` | Civil action number when present (e.g. "1:26-cv-11526") | | `body_html` | Full press release HTML | | `body_text` | Full press release plain text | ### Sample record ```json { "title": "Dunkin' Donuts Franchisees to Pay $250,000 in EEOC Disability Discrimination Suit", "url": "https://www.eeoc.gov/newsroom/dunkin-donuts-franchisees-pay-250000-eeoc-disability-discrimination-suit", "date": "June 5, 2026", "press_release_type": "Press release", "district_office": "New York District Office", "respondent_employer": "Dunkin' Donuts Franchisees", "settlement_amount_usd": 250000, "discrimination_type": ["disability"], "statute_cited": ["ADA"], "case_number": "1:26-cv-11526-AK", "body_text": "BOSTON – The Daly/Kenney Group, LLC and 15 related companies..." } ```` ### Input options | Field | Type | Default | Description | |---|---|---|---| | `maxItems` | integer | 10 | Maximum records to scrape (0 = all) | | `pressReleaseType` | string | All | Filter: All, Press Release, Litigation, Settlement | | `searchQuery` | string | — | Keyword search (e.g. "disability" or "Walmart") | ### Use cases - **EPLI insurers** — screen employers by discrimination history and settlement exposure before underwriting - **Labor & employment law firms** — track recent litigation outcomes and peer settlements by discrimination category - **Corporate compliance** — benchmark enforcement trends by statute, district, and employer size - **HR risk platforms** — build employer risk scores from EEOC settlement history ### Coverage The EEOC newsroom contains 10,000+ press releases dating back to the 1990s, covering all 53 EEOC field/district offices. Each discrimination category (disability, age, race, sex, religion, pregnancy, retaliation) and key statutes (ADA, Title VII, ADEA, GINA) are auto-classified from the press release body text. ### Technical notes Scrapes the public EEOC Drupal site via HTTP. No login, no proxy, no browser rendering required. Pagination via standard Drupal Views `?page=N` query parameter. # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `maxItems` (type: `integer`): Maximum number of press releases to scrape. Leave blank or set 0 to scrape all available records. ## `pressReleaseType` (type: `string`): Filter by press release type: All, Press Release, Litigation, Settlement ## `searchQuery` (type: `string`): Optional keyword search to filter press releases (leave blank for all records) ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "pressReleaseType": "All" } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "pressReleaseType": "All" }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/eeoc-enforcement-litigation-newsroom-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "pressReleaseType": "All", } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/eeoc-enforcement-litigation-newsroom-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "maxItems": 10, "pressReleaseType": "All" }' | apify call jungle_synthesizer/eeoc-enforcement-litigation-newsroom-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/eeoc-enforcement-litigation-newsroom-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "EEOC Enforcement & Litigation Newsroom Scraper", "description": "Scrapes EEOC enforcement press releases. Extracts employer name, settlement amounts, discrimination type, statute cited (ADA/Title VII/ADEA), district office, and case numbers — turning EEOC newsroom into structured employment-risk records.", "version": "0.1", "x-build-id": "sMPs6gPHmgYohjPbE" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~eeoc-enforcement-litigation-newsroom-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-eeoc-enforcement-litigation-newsroom-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jungle_synthesizer~eeoc-enforcement-litigation-newsroom-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-eeoc-enforcement-litigation-newsroom-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jungle_synthesizer~eeoc-enforcement-litigation-newsroom-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-eeoc-enforcement-litigation-newsroom-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "maxItems" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of press releases to scrape. Leave blank or set 0 to scrape all available records." }, "pressReleaseType": { "title": "Press Release Type", "enum": [ "All", "Press Release", "Litigation", "Settlement" ], "type": "string", "description": "Filter by press release type: All, Press Release, Litigation, Settlement" }, "searchQuery": { "title": "Search Query", "type": "string", "description": "Optional keyword search to filter press releases (leave blank for all records)" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```