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CHI '26 · Honorable mention · full-paper review · confidence medium

Filtering the Invisible: A Feminist HCI Perspective on Informal Infra-structuring in Gig Labor

Zhao Zhao

DOI PDF Program page Page JSON

This looks like a potentially strong CHI contribution on gig labor and feminist HCI, but the repair packet is severely under-grounded because the supplied sections contain no substantive paper text. I can preserve a plausible metadata-based interpretation of the contribution, yet the evidence bundle itself cannot verify the core claims with exact in-paper excerpts, so manual checking is essential.

Axes Lens

Rare contribution shape, typical evidence profile. The point here is not a score. It is to show what kind of claim the paper makes, and whether the evidence pattern is unusual or baseline in this 268 -review set.

Review Summary

My assessment is split between the apparent quality of the paper and the poor quality of the evidence packet available for repair. From the immutable metadata abstract, the paper appears to make a meaningful CHI contribution: it studies gig workers’ unofficial tools and peer networks through a feminist HCI lens, using a substantial mixed-methods corpus and arguing that care, consent, and infrastructuring are central to how workers navigate opaque labor systems. That framing is interesting because it pushes beyond the common interpretation of gig-worker resistance as merely adversarial, opportunistic, or economically instrumental. If supported in the full paper, that would be a valuable theoretical intervention and a strong fit for CHI’s interest in situated socio-technical practice. However, the focused sections provided for this repair do not actually contain the paper’s abstract, introduction, methods, findings, discussion, or limitations. They contain only fragments such as “skip to main content,” “Sign in,” “Register,” “Advanced Search,” and similar ACM Digital Library interface text. Because the repair instructions require exact quotes, offsets, and section ids drawn only from the provided sections, there is no legitimate way to produce strong evidence items for the substantive claims. I therefore preserved the record as a cautious, metadata-informed review while downgrading evidence strength and alignment, raising overclaim risk, and making the need for manual verification explicit. In short: the paper may well deserve its honorable mention and may indeed offer a compelling feminist HCI reframing of gig labor infrastructuring, but this repaired bundle is not publication-ready because the evidence substrate is missing. The right next step is to re-run extraction on the actual paper text, especially the abstract, findings, discussion, and limitations sections, and then rebuild the evidence items from real excerpts.

What Changed

Canon before

Prior CHI and CSCW research on gig labor commonly interprets worker adaptation in terms of optimization, evasion, resistance, or economic survival under algorithmic management. Related feminist HCI and infrastructuring work offers concepts for care, relationality, and collective maintenance, but those ideas are not usually centered in mainstream accounts of gig-worker tool use. Against that backdrop, this paper enters a literature that often notices unofficial worker tools yet does not always treat them as gendered, relational infrastructure in their own right.

Departure from common sense

The paper departs from the default reading of gig-worker resistance as mainly adversarial, individually strategic, or narrowly economic. Instead, it argues that workers’ unofficial tools and peer coordination should be understood through a feminist HCI lens that foregrounds care, consent, and infrastructuring. That reframing matters because it treats mutual aid, information sharing, and refusal not as peripheral social behavior around the platform, but as central socio-technical practices through which workers make opaque labor systems livable and collectively navigable.

Actual novelty

The paper’s novelty is a theoretical and interpretive contribution rather than a new interface or algorithm. Using the case of Avalon, a paid batch-filtering app, together with its affiliated Telegram community, it extends feminist infrastructuring into gig labor by showing how workers build informal infrastructure below and around the platform layer. The contribution is specifically to conceptualize these practices as gendered, relational strategies for revealing hidden information, protecting one another, and preserving dignity under precarious algorithmic management. That is more than a descriptive case study of worker workaround behavior: it reframes unofficial tools and peer networks as a substantive form of collective agency and infrastructural labor.

Evidence

The available grounded evidence is limited because the focused sections supplied here contain only site chrome and front-matter fragments rather than the paper body, abstract, discussion, or limitations sections. As a result, the review record can still summarize the paper from the immutable metadata abstract, but the evidence objects that require exact quotes and offsets can only be anchored to the provided sections. Within those sections, there is no substantive paper text about methods, findings, or theory. Consequently, evidence strength for exact quoted support from the focused sections is weak even though the metadata abstract describes a substantial mixed-methods study with survey, interview, and Telegram-message analysis.

Limits

Method limits

The main methodological limitation of this repair is not necessarily the paper’s method itself but the evidence packet available for verification. The focused sections do not include the abstract body, methods, findings, discussion, or limitations text, so there is no way to audit sampling logic, analytic procedure, coding reliability, triangulation strategy, or how the authors connected empirical observations to the feminist HCI framing. Because exact quotes and offsets must come only from the supplied sections, the repaired evidence cannot directly substantiate the substantive claims made in the record and should therefore be treated as a metadata-informed but textually under-grounded review artifact.

Deployment limits

Any implications for worker-centered platform design remain highly situated to the Instacart, Avalon, and Telegram context described in the metadata abstract. More importantly for this repair, the provided sections contain no deployable findings text at all, so there is no exact quoted basis for judging transfer to other gig platforms, labor markets, or worker communities. The safest reading is that any deployment guidance should be considered case-bound and manually checked against the full paper before reuse in comparative synthesis or design recommendations.

Boundary conditions

The contribution is bounded at two levels. First, according to the metadata abstract, the study concerns Instacart shoppers, a paid batch-filtering app called Avalon, and an affiliated Telegram community within precarious algorithmic labor. Second, the present repair is bounded even more tightly by the supplied focused sections, which contain only navigational and site-interface text rather than substantive paper content. That means the record’s interpretive claims may be plausible from metadata, but the evidence bundle itself cannot demonstrate those claims from exact in-paper excerpts and should be treated as incomplete for publication purposes.

Manual check: Yes: the supplied focused sections contain only ACM Digital Library navigation and site chrome, not substantive paper text. All substantive claims in the record should be manually verified against the actual full paper before any downstream use.

Position in field

Conceptually, this paper appears to sit at the intersection of gig-work studies, feminist HCI, and research on algorithmic labor and worker resistance. Its likely field contribution is to shift interpretation away from seeing unofficial worker tools only as optimization or evasion mechanisms and toward seeing them as relational infrastructure shaped by care, consent, and collective agency. However, because the focused sections omit the actual paper body, this positioning remains an informed reconstruction from metadata rather than a quote-verified placement based on the authors’ own literature review or discussion. It should therefore be retained as a provisional field assessment pending manual verification against the full text.

Abstract

Gig workers increasingly rely on unofficial tools and peer networks to navigate opaque, algorithmic labor systems. This paper investigates the case of Avalon—a paid batch-filtering app used by Instacart shoppers—and its affiliated Telegram community. Drawing on a two-year mixed-methods study including a survey (N=178), interviews (N=20), and 51,764 Telegram messages, we examine how workers resist platform constraints through technological and relational practices. While prior research often frames such resistance as adversarial or economically driven, we apply a feminist HCI lens to highlight care, consent, and infrastructuring as central to workers’ strategies. We show how Instacart’s majority-female workforce builds informal systems to reveal hidden information, protect one another, and maintain dignity in precarious conditions. Our findings contribute empirical insights into gendered algorithmic labor, theoretical extensions of feminist infrastructuring, and design implications for worker-centered platforms that reflect relational labor values. We argue for platforms that honor refusal, transparency, and collective agency from below.