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Field
Primary Outcomes (Explanation)
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Before
Take-up: We measure take-up of the reminder using two proxy indicators:
(1) Whether the reminder was successfully sent, and
(2) Whether any recipient clicked on the survey link or the opt-out link.
Message Features:
Our primary measure is message toxicity, assessed using the Detoxify model’s toxicity score. We also examine message positivity (by SiEBERT) and constructiveness (identified by GPT-4o).
Activities:
We distinguish between communication-related activities (e.g., comments) and productivity-related activities (e.g., lines of code, pull requests, and commits). For primary outcomes, we focus on (1) number of comments, (2) lines of code submitted, and (3) share of code accepted (as defined as lines of code accepted / total lines of code submitted).
Effects will be estimated using difference-in-differences (DiD) and event-study (ES) specifications, as described below.
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After
Take-up: We measure take-up of the reminder using two proxy indicators:
(1) Whether the reminder was successfully sent, and
(2) Whether any recipient clicked on the survey link or the opt-out link.
Message Features:
Our primary measure is message toxicity, assessed using the Detoxify model’s toxicity score. We also examine message positivity (by SiEBERT) and constructiveness (identified by GPT-4o).
Activities:
We distinguish between communication-related activities (e.g., comments) and productivity-related activities (e.g., lines of code, pull requests, and commits). We primarily focus on (1) total number of activities, and (2) number of messages sent. We will also look at productivity measures: (1) lines of code submitted, and (2) share of code accepted (as defined as lines of code accepted / total lines of code submitted).
Effects will be estimated using difference-in-differences (DiD) and event-study (ES) specifications, as described below.
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