Anthropic Economic Index: Insights from Claude 3.7 Sonnet

Analysis Replication Notebook

This notebook contains the code used to produce the visualizations and analysis for the Anthropic Economic Index report based on Claude 3.7 Sonnet data. It analyzes how different occupations interact with AI systems through automation and augmentation patterns derived from real-world usage data.

Data Files in this Directory

cluster_level_dataset: A folder containing data released at the cluster level, including mappings to O*NET tasks, automation vs. augmentation, and "extended thinking" mode fraction
onet_task_statements.csv: Contains O*NET task statements with their associated occupational codes
SOC_Structure.csv: Standard Occupational Classification (SOC) structure data with major group codes and titles
task_pct_v1.csv: Version 1 of task percentage data
task_pct_v2.csv: Version 2 of task percentage data (current)
automation_vs_augmentation_by_task.csv: Data on automation vs. augmentation classifications by task
automation_vs_augmentation_v1.csv: Version 1 of automation vs. augmentation interaction type data
automation_vs_augmentation_v2.csv: Version 2 of automation vs. augmentation interaction type data
task_thinking_fractions.csv: Fraction of each O*NET task with its associated "extended thinking" mode fraction

Data Dictionary

onet_task_statements.csv

Field	Description
O*NET-SOC Code	Occupational code from the O*NET-SOC system
Title	Occupational title
Task	Description of specific occupational task

SOC_Structure.csv

Field	Description
Major Group	Two-digit code identifying major occupational group
SOC or O*NET-SOC 2019 Title	Title of the major occupational group

task_pct_v1.csv and task_pct_v2.csv

Field	Description
task_name	Normalized name of the task
pct	Percentage of task prevalence in dataset

automation_vs_augmentation_by_task.csv

Field	Description
task_name	Normalized name of the task
directive	Ratio indicating directive automation pattern (0-1)
feedback_loop	Ratio indicating feedback loop automation pattern (0-1)
validation	Ratio indicating validation augmentation pattern (0-1)
task_iteration	Ratio indicating task iteration augmentation pattern (0-1)
learning	Ratio indicating learning augmentation pattern (0-1)
filtered	Ratio indicating filtered (excluded) tasks (0-1)

automation_vs_augmentation_v1.csv and automation_vs_augmentation_v2.csv

Field	Description
interaction_type	Type of interaction (directive, feedback loop, validation, task iteration, learning, none)
pct	Percentage of this interaction type in the dataset

task_thinking_fractions.csv

Field	Description
task_name	Normalized name of the task
thinking_fraction	Ratio of this task that used extended thinking mode

Running the analysis

Open v2_report_replication.ipynb in a notebook editor and run the cells in order.