# "Is This Not Enough?": Asymmetries in Institutional Accountability and Collective Sensemaking in the Case of Canada's Algorithmic Visa Triage System

arXiv: https://arxiv.org/abs/2606.13071 · HTML: https://mlsanity.com/paper/2606.13071/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 19 of its 92 references that are in the map.
- First posted on arXiv 11 Jun 2026.

## Builds on (most cited first, 19 of 19)

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- [Rethinking "Risk" in Algorithmic Systems Through A Computational Narrative Analysis of Casenotes in Child-Welfare](https://mlsanity.com/paper/2302.08497/) (2023)
- [The DSA Transparency Database: Auditing Self-reported Moderation Actions by Social Media](https://mlsanity.com/paper/2312.10269/) (2023)
- [Automated Transparency: A Legal and Empirical Analysis of the Digital Services Act Transparency Database](https://mlsanity.com/paper/2404.02894/) (2024)
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- [Immigration Document Classification and Automated Response Generation](https://mlsanity.com/paper/2010.01997/) (2020)

## Built on by (most cited first, 1 of 1)

- [A Global Comparison of Schemas, Transparency, and Interoperability in Public-Sector AI Registers and Inventories](https://mlsanity.com/paper/2609.24883/) (2026)

## Abstract (arXiv)

This paper examines how algorithmic accountability in Canada's visa system is articulated institutionally and experienced by applicants across borders. We analyzed Immigration, Refugees and Citizenship Canada (IRCC)'s Algorithmic Impact Assessment (AIA) for the temporary resident visa (TRV) triage system using the algorithmic decision-making adapted for the public sector (ADMAPS) framework and analyzed Reddit discussions among applicants using a mixed-methods approach. We show that while institutional artifacts emphasize transparency, procedural safeguards, and bounded impacts, applicants engage in collective sensemaking to interpret opaque decisions, often relying on peer knowledge amid uncertainty. We identify three asymmetries between how institutional accountability is structured and how people perceive the process: epistemic asymmetry in access to decision logic, jurisdictional asymmetry in exposure shaped by geopolitical positioning, and temporal--relational asymmetry in how waiting and uncertainty are experienced. We emphasize why it is important to shift attention from institutional design to the uneven distribution of experiences with public-sector algorithmic governance. Together, these contributions demonstrate how algorithmic governance systems in the context of transnational migration produce structured asymmetries not captured by institutional disclosure frameworks, and how extending ADMAPS can account for those uneven translations of accountability.