Enabling Sensitive Conversations with Consent Boundaries: Moa, a Platform for Discussing PhD Advising Relationships
Jane Im, Kentaro Toyama

TL;DR
Moa is a social media platform designed to facilitate sensitive PhD advising conversations by allowing users to define audience boundaries anonymously, promoting ally discovery and support.
Contribution
The paper introduces 'consent boundaries,' a novel feature enabling anonymous, flexible audience selection to improve ally discovery in sensitive contexts.
Findings
3-week field study with 47 users demonstrated effective facilitation of sensitive conversations.
22.6% of users utilized consent boundaries to define their audience.
The platform's features collectively supported ally discovery and supportive interactions.
Abstract
When an individual is harmed by someone in power, such as a workplace manager, it can help to identify allies--people who would offer sympathy, advice, or supportive action. However, ally discovery is fraught because the very people who might be most relevant--e.g., someone who reports to the same manager--might not be sympathetic and could potentially exacerbate the harm. We examine this problem in the specific context of PhD students navigating advising challenges and present a social media platform called "Moa" that brings together a number of features that we believe facilitate ally discovery. Moa's most novel element is an audience selection process that uses what we call consent boundaries, which allow users to flexibly define each post or comment's audience based on factors such as common social identity or lived experience, all while preserving anonymity--neither senders nor…
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