Large text corpora, such as Reddit posts, have become an increasingly prevalent site of qualitative inquiry. However, most large text corpora are intractable for qualitative researchers. Instead, teams rely on statistical subsampling to reduce corpora to a manageable size for qualitative analysis. While previous work for navigating large corpora involves visualizing the dataset at the corpus-level using high-level statistical summaries, few systems offer the ability to curate data using an interpretivist approach. To address this, we developed Teleoscope, a web-based interface designed to scaffold iterative, interactive, and reflexive refinement of a large corpus, in a process we call thematic curation. Across three deployments, we learned that Teleoscope supports serendipitous discovery of new keywords, results in greater feelings of confidence in search saturation, and aids collaborative discussion of alternative curation pathways. Teleoscope empowers researchers to stay "close to the data" in order to make qualitative workflows methodologically coherent with large text corpora.

Reflexive Thematic Analysis (RTA) is a critical method for generating deep interpretive insights. Yet its core tenets, including researcher reflexivity, tangible analytical evolution, and productive disagreement, are often poorly supported by software tools that prioritize speed and consensus over interpretive depth. To address this gap, we introduce Reflexis, a collaborative workspace that centers these practices. It supports reflexivity by integrating in-situ reflection prompts, makes code evolution transparent and tangible, and scaffolds collaborative interpretation by turning differences into productive, positionality-aware dialogue. Results from our paired-analyst study (N = 12) indicate that Reflexis encouraged participants toward more granular reflection and reframed disagreements as productive conversations. The evaluation also surfaced key design tensions, including a desire for higher-level, networked memos and more user control over the timing of proactive alerts. Reflexis contributes a design framework for tools that prioritize rigor and transparency to support deep, collaborative interpretation in an age of automation.

This paper explores the design challenges that arise in supporting online freelancers to navigate relationships with clients. Prior studies have shown that current platform designs can lead to worker precarity in freelancer-client relationships, such as power imbalances, information asymmetry, and labor abuse. To envision alternative designs that empower workers in managing their relationships with clients, we engaged 22 Upwork freelancers in participatory speculative design activities. Through this co-design process, we identified design tensions that constrain design options as a result of conflicting values and priorities that could only be balanced and compromised rather than completely resolved. Six design tensions were identified in the context of designing for four different phases of freelancing. We observed three patterns in these tensions: 1) the freelancers' need for client involvement in their tasks and career growth, which conflicted with their skepticism that clients had sufficient incentives to be involved; 2) that there was often no viable balancing option for some tensions, but they could be addressed through changes in the platform's incentive structure; and 3) some tensions occurred not only between freelancers and clients, but also within the freelancer community. We present three approaches for addressing these design tensions and discuss how this research can support more equitable and healthy freelancer-client relationships.

Digitally replicating the appearance and behaviour of individuals is becoming feasible with recent advancements in deep-learning technologies such as interactive deepfake applications, voice conversion, and virtual actors. Interactive applications of such agents, termed AI clones, pose risks related to impression management, identity abuse, and unhealthy dependencies. Identifying concerns AI clones will generate is a prerequisite to establishing the basis of discourse around how this technology will impact a source individual's selfhood and interpersonal relationships. We presented 20 participants of diverse ages and backgrounds with 8 speculative scenarios to explore their perception towards the concept of AI clones. We found that (1. doppelganger-phobia) the abusive potential of AI clones to exploit and displace the identity of an individual elicits negative emotional reactions; (2. identity fragmentation) creating replicas of a living individual threatens their cohesive self-perception and unique individuality; and (3. living memories) interacting with a clone of someone with whom the user has an existing relationship poses risks of misrepresenting the individual or developing over-attachment to the clone. These findings provide an avenue to discuss preliminary ethical implications, respect for identity and authenticity, and design recommendations for creating AI clones.