RAD Bulk Decisions Dataset

Description: This is a bulk open-access dataset in JSON format with the full text of all Immigration and Refugee Board (IRB) Refugee Appeal Division cases provided by the IRB to the Refugee Law Lab. The process through which data is collected and processed, as well as code snippets for loading the data, are available in a repository on the Refugee Law Lab Github.

Data: https://github.com/Refugee-Law-Lab/rad_bulk_data/blob/master/DATA/yearly

Code Repository: https://github.com/Refugee-Law-Lab/rad_bulk_data

Current Coverage: 2013-Present

Number of Decisions: ~27,000

Languages: English & French

Format: JSON, Parquet, Hugging Face Dataset

License: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)

Citation: Sean Rehaag, “RAD Bulk Decisions Dataset” (2023), online: Refugee Law Laboratory https://refugeelab.ca/bulk-data/rad

Programmatic Access in Python (via Hugging Face Datasets):

from datasets import load_dataset
import pandas as pd

dataset = load_dataset("refugee-law-lab/canadian-legal-data", "RAD", split="train")

# convert to dataframe
df = pd.DataFrame(dataset)
df

Programmatic Access to in Python (via Parquet):

import pandas as pd
import requests
from io import BytesIO

url = 'https://huggingface.co/datasets/refugee-law-lab/canadian-legal-data/resolve/main/RAD/train.parquet'

# load data
results = requests.get(url)

# convert to dataframe
df = pd.read_parquet(BytesIO(results.content))
df

Programmatic Access in Python (JSON via GitHub):

import pandas as pd
import requests
import json

start_year = 2013 # First year of data sought (2013+)
end_year = 2023 # Last year of data sought (2023 -)
base_ulr = 'https://raw.githubusercontent.com/Refugee-Law-Lab/rad_bulk_data/master/DATA/YEARLY/' 

data results = [] 
     for year in range(start_year, end_year+1): 
     url = base_ulr + f'{year}.json'
     results.extend(requests.get(url).json()) 

df = pd.DataFrame(results)
df