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arxiv: 2604.18121 · v1 · submitted 2026-04-20 · 💻 cs.HC · cs.SI

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

Jane Im , Kentaro Toyama This is my paper

Pith reviewed 2026-05-10 04:10 UTC · model grok-4.3

classification 💻 cs.HC cs.SI
keywords consent boundariesally discoveryPhD advisinganonymous communicationsensitive conversationssocial media platformpower dynamicsfield study
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0 comments X

The pith

Moa introduces consent boundaries to let PhD students reach sympathetic audiences about advising issues while preserving full anonymity.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper shows how a platform can solve the problem of finding allies in power-imbalanced relationships without risking further harm from unsympathetic readers. It does this through a set of features centered on consent boundaries, which let users define each post's audience by shared identity or experience without anyone learning identities. A three-week study with 47 real PhD students found the combined features supported sensitive conversations, and over one-fifth of users chose to apply consent boundaries. This approach matters because traditional anonymous posting either reaches no one useful or risks exposure, while direct targeting can reveal who is posting. The work also sketches a general recipe for building ally-discovery systems that prioritize consent.

Core claim

Moa combines anonymity with consent boundaries—an audience selection method that matches posts to readers based on common social identity or lived experience—allowing PhD students to discuss advising challenges with potentially sympathetic people without senders or recipients learning each other's identities, as shown by a field study in which the features together enabled such conversations and 22.6 percent of participants used the boundaries.

What carries the argument

Consent boundaries: the audience selection process that defines each post or comment's recipients according to factors such as shared identity or experience while guaranteeing that neither senders nor recipients learn identities.

If this is right

  • The platform's features together enabled sensitive conversations about PhD advising relationships.
  • 22.6 percent of the 47 study participants actively used consent boundaries for their posts.
  • A consent-centered design provides measurable benefits for safe ally discovery in power-imbalanced settings.
  • The overall set of mechanisms supplies a reusable recipe for other systems intended to support ally discovery.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • The same consent-boundary approach could be tested in adjacent domains such as workplace reporting or academic peer support where power differentials create similar risks.
  • Longer-term studies might reveal whether repeated use of identity-based filters leads users to self-sort into narrower groups than intended.
  • Integrating consent boundaries into existing university or professional networks could lower the barrier for students who hesitate to create new accounts.

Load-bearing premise

That users can correctly specify audiences using self-reported identity or experience so that the post reaches sympathetic readers without allowing unintended recipients to infer the sender's identity.

What would settle it

A deployment in which users who set consent boundaries report receiving responses from non-supportive readers or detect that their identity was inferred from the chosen audience criteria would falsify the claim.

Figures

Figures reproduced from arXiv: 2604.18121 by Jane Im, Kentaro Toyama.

Figure 1
Figure 1. Figure 1: Moa is a social platform that incorporates a novel concept we call a [PITH_FULL_IMAGE:figures/full_fig_p002_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: A user (@po1r3) set their post to be visible to those who are international PhD students, not advised [PITH_FULL_IMAGE:figures/full_fig_p010_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: Different dimensions of consent boundary. The high-level categories included: identity, challenges [PITH_FULL_IMAGE:figures/full_fig_p011_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Users can also set a consent boundary for each comment. @abc123 shows their comment to users who [PITH_FULL_IMAGE:figures/full_fig_p012_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: The first graph shows Moa’s daily post and comment volume, the second shows daily post views, and [PITH_FULL_IMAGE:figures/full_fig_p015_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: Results of the post-study survey (1=Strongly disagree/dissatisfied; 5=Strongly agree/satisfied). Partici [PITH_FULL_IMAGE:figures/full_fig_p016_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: Example designs that show a system for enabling PhD students to connect around advising challenges. [PITH_FULL_IMAGE:figures/full_fig_p030_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Users can restrict a post or comment’s consent boundary. [PITH_FULL_IMAGE:figures/full_fig_p031_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Moa’s landing page. Proc. ACM Hum.-Comput. Interact., Vol. 1, No. 1, Article . Publication date: April 2026 [PITH_FULL_IMAGE:figures/full_fig_p031_9.png] view at source ↗
Figure 10
Figure 10. Figure 10: Moa’s sign-up page. Users are asked to voluntarily submit identity-related information, PhD program, advisor names, and challenges experienced in advising relationships. Proc. ACM Hum.-Comput. Interact., Vol. 1, No. 1, Article . Publication date: April 2026 [PITH_FULL_IMAGE:figures/full_fig_p032_10.png] view at source ↗
Figure 11
Figure 11. Figure 11: Users can update their identity traits and experiences on Moa in the account settings page. [PITH_FULL_IMAGE:figures/full_fig_p033_11.png] view at source ↗
read the original 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 recipients learn each other's identities, even as the post reaches the right audience. A 3-week field study with 47 real-world users showed that the features in combination facilitated sensitive conversations about advising, with 22.6% of users using consent boundaries. We discuss both our overall "recipe" for systems for ally discovery and the benefits of a consent-centered approach to design.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The paper presents Moa, a social media platform for PhD students discussing advising challenges. Its core innovation is 'consent boundaries,' an audience-selection mechanism allowing posts to be targeted at users sharing specific identities or lived experiences while preserving mutual anonymity. A 3-week field study with 47 real-world users is reported, with 22.6% of participants using consent boundaries; the authors claim the combined features facilitated sensitive conversations about advising relationships and offer a general 'recipe' for ally-discovery systems.

Significance. If the anonymity guarantees hold and the field study provides credible evidence of facilitation beyond self-report, the work could meaningfully advance HCI research on consent, privacy-preserving audience control, and support mechanisms in power-imbalanced settings such as academia. The use of a real-world deployment with actual usage data is a positive aspect.

major comments (2)
  1. [Consent boundaries description] The description of consent boundaries (likely §3) states that audiences are defined flexibly by common social identity or lived experience while preserving anonymity, yet supplies no matching protocol, trusted-third-party assumptions, or analysis showing that the recipient set cannot be used to infer sender identity when attributes are sparse or unique. This directly undermines the central claim that posts reach sympathetic recipients without leakage risk.
  2. [Field study / Evaluation] The field study section reports 22.6% usage of consent boundaries and claims facilitation of sensitive conversations, but provides no details on recruitment, participant screening, controls for self-selection, survey instruments, or qualitative analysis depth. The evaluation rests entirely on self-reported usage statistics without logs, external validation, or checks for perceived leakage, weakening the soundness of the empirical support for the platform's effectiveness.
minor comments (1)
  1. [Abstract] The abstract claims the features 'in combination facilitated sensitive conversations' but does not preview any quantitative or qualitative metrics beyond the single usage percentage; adding a brief indication of what 'facilitated' was measured by would improve clarity.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for their constructive and detailed feedback, which highlights important areas for strengthening the paper's claims on privacy and evaluation rigor. We address each major comment below and indicate revisions to the manuscript.

read point-by-point responses

  1. Referee: [Consent boundaries description] The description of consent boundaries (likely §3) states that audiences are defined flexibly by common social identity or lived experience while preserving anonymity, yet supplies no matching protocol, trusted-third-party assumptions, or analysis showing that the recipient set cannot be used to infer sender identity when attributes are sparse or unique. This directly undermines the central claim that posts reach sympathetic recipients without leakage risk.

    Authors: We appreciate the referee pointing out this gap in the technical description. The current manuscript focuses on the user-facing design and high-level anonymity properties of consent boundaries but does not provide a formal protocol, explicit trusted-third-party assumptions, or a privacy analysis for edge cases such as sparse attributes. In the revised version, we will expand the relevant section (likely §3) to include: (1) a description of the matching protocol using a central server that computes audience eligibility via attribute intersection without exposing individual user data or identities; (2) the assumption of a trusted platform operator (standard for deployed social systems); and (3) a discussion of potential inference risks when attributes are unique or sparse, including proposed mitigations such as minimum audience size requirements and attribute generalization. These additions will better ground the anonymity claims. revision: yes

  2. Referee: [Field study / Evaluation] The field study section reports 22.6% usage of consent boundaries and claims facilitation of sensitive conversations, but provides no details on recruitment, participant screening, controls for self-selection, survey instruments, or qualitative analysis depth. The evaluation rests entirely on self-reported usage statistics without logs, external validation, or checks for perceived leakage, weakening the soundness of the empirical support for the platform's effectiveness.

    Authors: We agree that additional methodological transparency is required. We will revise the field study section to include: recruitment details (targeted outreach via university PhD student organizations, mailing lists, and relevant forums, following IRB approval); screening criteria (confirmation of current PhD status and interest in advising topics); explicit discussion of self-selection as a limitation of the exploratory deployment; the survey instruments (pre/post questionnaires with Likert items on perceived safety and conversation facilitation, plus open-ended qualitative prompts); and depth of qualitative analysis (thematic coding of responses). The 22.6% figure derives from platform usage logs tracking posts that employed consent boundaries, and we will add more granular log-derived statistics. We acknowledge the absence of control conditions, external validation, or direct leakage perception checks as inherent limitations of this real-world field study design and will state them clearly. These changes will improve the soundness of the empirical claims. revision: yes

Circularity Check

0 steps flagged

No circularity: empirical system evaluation with independent field study

full rationale

The paper introduces the Moa platform and consent boundaries as a design contribution for ally discovery in PhD advising contexts, then reports results from a 3-week field study with 47 users showing 22.6% usage of the feature. There are no equations, fitted parameters, predictions, or derivation chains that reduce to prior inputs. The evaluation relies on direct user data rather than self-citations or definitional loops. The central claims rest on the observed usage rates and qualitative feedback from the study, which are independent of the system's description. No load-bearing self-citations, ansatzes, or renamings of known results appear in the provided text.

Axiom & Free-Parameter Ledger

0 free parameters · 2 axioms · 1 invented entities

The work is design-oriented and empirical; no mathematical free parameters or derivations are present. The central claim rests on assumptions about user behavior and the effectiveness of self-selected identity matching.

axioms (2)
  • domain assumption Users can accurately self-identify relevant social identities or lived experiences for audience targeting
    Implicit in the consent boundary design and the claim that it reaches the right audience.
  • domain assumption Anonymity is preserved even when posts reach targeted recipients
    Stated as a core property of the system.
invented entities (1)
  • consent boundaries no independent evidence
    purpose: Flexible audience definition based on common social identity or lived experience while preserving anonymity
    Introduced as the most novel element of the Moa platform.

pith-pipeline@v0.9.0 · 5516 in / 1065 out tokens · 29422 ms · 2026-05-10T04:10:21.116007+00:00 · methodology

discussion (0)

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