The Domestic Operating System: An Empirical Investigation of Digital Technology and Hidden Work in the Home

Sarah Lucy Frampton, Sandy J.J. Gould and Anna L. Cox

This is a pre-print HTML author version of the paper. The ACM-published version will be available open access from the ACM and is available [here as a PDF]({{ ref papers/The_Domestic_Operating_System.pdf}}). Please cite the work as:

Sarah Lucy Frampton, Sandy J.J. Gould, and Anna L. Cox. 2026. The Domestic Operating System: An Empirical Investigation of Digital Technology and Hidden Work in the Home. In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI ‘26), April 13–17, 2026, Barcelona, Spain. ACM, New York, NY, USA. https://doi.org/10.1145/3772318.3791167

Abstract

Digital technologies play a role in the cognitive work of managing households, yet much of this labour remains invisible, making it harder to share, delegate, or value. Existing tools support household tasks but focus on visible activities such as chores or planning, leaving unclear how hidden domestic labour is supported. To address this, we surveyed 50 participants and conducted qualitative analysis. We found that value-driven labour, such as managing household vision and values, shapes other labours yet remains least visible and hardest to delegate. Domains like inclusion and special events appear salient in everyday life yet remain largely unsupported by current tools. We found that while family management is collaborative, most tools remain oriented to single users. We contribute an empirical mapping of digital support and gaps across six forms of family management labour, and offer a foundation for anticipating how emerging domestic technologies may support or inadvertently reshape this work.

Keywords: Family management labour; Hidden labour; Household coordination; Domestic technology design; Feminist HCI

Introduction

Digital technologies increasingly mediate the work of managing households, from personal productivity tools to smart home systems. Many tools support visible, physical domestic tasks such as cooking, cleaning, or childcare, for example, a smart washing machine that sends a notification when a cycle ends [Cowan 1983; Strengers 2021]. While such features address the mechanical task, they leave untouched the hidden layers of labour that surround laundry. Beyond folding or putting clothes away, this labour involves anticipating when items are needed, balancing competing priorities (e.g., school uniforms versus work clothes), responding to disruptions such as spills or weather changes, and negotiating standards of cleanliness within the household. These activities involve subtle value-driven judgements and continual replanning, yet remain largely unsupported by current technologies.

Some of these cognitive labours, such as financial planning and scheduling, are increasingly acknowledged in HCI and addressed by widely adopted tools like banking apps and shared calendars [Sannon and Cosley 2020; Kalms et al. 2008]. However, other forms of family management labour remain conceptually and practically underexplored. Feminist and sociological researchers have begun to define and categorise these labours [Robertson et al. 2019; Daminger 2022; Reich-Stiebert et al. 2023], while technology scholars have shown that domestic technologies can both obscure and exacerbate household dynamics, introducing new burdens, reinforcing outdated norms, or encoding structural inequalities [Perez 2019; Strengers 2021; Kennedy et al. 2015].

The failure to adequately value, support, or redistribute hidden cognitive labour has been linked to significant personal and societal costs [Offer 2014; Haupt and Löbl 2022; Ruppanner et al. 2020]. While prior work in HCI has offered knowledge that supports important interventions into family collaboration, personal information management (PIM), automation and smart home design [Plaisant et al. 2006; Brush et al. 2007; Neustaedter et al. 2006; Hertog et al. 2023], there is limited research into how technologies such as smart home systems, family productivity apps, and AI-assisted services interact with the full range of domestic cognitive labour, particularly its emotional, value-driven, and less structured aspects.

As concerns about care, time scarcity and household coordination gain visibility in policy, media and commercial discourse, digital systems are increasingly promoted as solutions to domestic pressure [Hertog et al. 2023]. Histories of domestic automation show that technologies repeatedly enter the home with the promise of easing this strain, even as they tend to reframe rather than remove underlying labour [Hester and Srnicek 2023; Strengers 2021]. Contemporary smart home systems, family productivity apps and AI-assisted services extend this trajectory: they offer assistance with planning, scheduling and monitoring but do not engage with the anticipatory, interpretative and value-driven work that organises everyday family life.

This paper addresses that gap. We investigate six distinct forms of hidden family management labour, drawing on sociological and feminist taxonomies to structure a qualitative survey of 50 participants. We analysed responses using two complementary approaches: a content analysis to compare participant experiences against existing taxonomies, and a thematic analysis to surface broader patterns in how technologies are used, avoided, or emotionally experienced. We contribute empirical insights by surfacing participants’ accounts of value-driven meta-labour, described here as Life-Crafting, the ongoing work of managing household vision and values, and how they describe it as coordinating and shaping other forms of family work. We show that participants often describe family management as collaborative, while the tools participants used are commonly individualised.

Positionality Statement

Our research is driven by a desire to use technology to improve equality and quality of life within the domestic space. We share a widely held feminist belief that gender is largely a social construct, one that has a role in shaping and is shaped by technology. Each of us, in our own way, identifies as a family manager, by which we mean those who take on the cognitive and emotional work of coordinating family life [Robertson et al. 2019]. This positionality shaped the questions we asked, the examples we attended to, and how we interpreted both enjoyment and burden in participants’ accounts.

Background and Related Work

Cognitive and Emotional Labour in the Home

While domestic labour is often associated with physical tasks such as cooking, cleaning, and childcare, feminist and sociological research draws attention to the cognitive and emotional work that also sustains family life. Here, “family” is understood broadly, including nuclear, blended, same-sex, single-parent, or multi-species households with pets [Hull et al. 2019; Manning et al. 2020; Solhjoo et al. 2022]. We focus on the cognitive and emotional labours carried out by those who see themselves as family managers. Following Robertson et al. [2019], we define family management labour as “family-related mental labour,” or more broadly, “thinking performed for the sake of accomplishing family goals.” Prior research often refers to this as the gendered mental load, reflecting its unequal distribution and historical association with women [Ciciolla and Luthar 2019; Daminger 2020; Offer 2014]. We use the term family management labour to avoid reinforcing gendering, while still recognising its history and dynamics.

Two related concepts underpin this work. Cognitive labour in the family context includes anticipating needs, generating options, making decisions, and monitoring outcomes, often invisible and mentally taxing [Daminger 2020; Haupt and Löbl 2022; Ciciolla and Luthar 2019]. Emotional labour describes managing one’s own and others’ emotions to maintain family harmony, likewise invisible and unequally distributed, often falling to women and marginalised groups [Hackman 2023; Rosewell et al. 2022].

These less visible forms of labour include planning meals, managing schedules, anticipating needs, and monitoring wellbeing [Sannon and Cosley 2020; Kalms et al. 2008]. They are typically hidden because they are mental, embedded in other activities, and anticipatory rather than reactive [Daminger 2020]. Scholars argue that this invisibility matters because it obscures the scale and complexity of the work, making it harder to recognise, value, and share [Reich-Stiebert et al. 2023].

Sociological research has begun to develop taxonomies [Robertson et al. 2019; Reich-Stiebert et al. 2023; Daminger 2022] and typologies [Weeks and Ruppanner 2024] to define these forms of labour. Robertson et al. [2019] offer a taxonomy of discrete labour forms spanning both cognitive and emotional, elicited from focus groups with mothers, which we use to structure our survey (see Table 1).

Table 1: Robertson et al.’s labour types [2019]. This framework represents both seen (e.g., delegating) and unseen tasks (e.g., anticipating needs) but all refer to work that is largely internal.

Although Robertson et al.’s study focused on mothers, the taxonomy and labour types they describe are not exclusive to parenting activities. Only the category of Metaparenting directly references parenting, but the term more broadly concerns curating shared values and visions. In this broader sense, Metaparenting shares features with adjacent literatures such as Life-Crafting [van Zyl et al. 2023], Job Crafting [Mukherjee et al. 2023], and Conservation of Resources (COR) theory [Halbesleben et al. 2014], which all explore how people define meaningful goals and invest effort in their pursuit.

Technologies in the Home

Digital technologies increasingly shape how family management labour is organised, distributed, and understood. From smart home devices and automation tools to calendars and wellness trackers, these systems can both enable and complicate household coordination.

Historical critiques remind us that these paradoxes are not new. Cowan’s More Work for Mother [1983] showed how washing machines and stoves reshaped rather than reduced household labour. Contemporary critiques echo these dynamics. Sadowski [2024] argues that smart home devices serve platform companies more than households, reducing some labour while creating new invisible ones. Similarly, feminised voice assistants reproduce submissive stereotypes and care roles [Strengers 2021], and smart systems marketed as convenient often demand maintenance and troubleshooting [Whiting et al. 2020; Kennedy et al. 2015].

Hester and Srnicek’s history of domestic technology [2023] further illustrates how automation often reframes, rather than removes, domestic labour. They argue that many contemporary systems alleviate only minor frictions, while more meaningful or value-laden tasks remain unchanged or become more demanding.

Research on AI in domestic contexts shows that it risks repeating the same flawed premises as earlier domestic technologies. Hertog et al. [2023] explore the potential of AI for household support but focus on time savings from automating physical tasks, while overlooking the cognitive and value-driven coordination that makes these tasks possible. As Perez [2019] demonstrates, AI systems are built on partial and biased data, meaning that domestic AI is likely to reproduce inequality and obscure hidden labours rather than alleviate them.

Within HCI, attention to cognitive labour has emerged through fields such as Personal Task Management (PTM) [Kamsin et al. 2014; Ahmetoglu et al. 2024], Personal and Family Information Management (PIM/FIM) [Jones 2021; Sannon and Cosley 2020], and Personal Health Information Management (PHIM) [Werner et al. 2018].

Taken together, existing research shows that domestic technologies, whether historical, smart, or AI-driven, often obscure, shift, or complicate the labours they claim to support. Despite longstanding critiques, the home remains a space where digital systems continue to be introduced, adopted and normalised—including through the rapid expansion of AI systems and smart homes [Andriulo et al. 2024; Strengers 2021].

Research Questions

Our three research questions are:

RQ1 Which specific labours identified in this study align with, or diverge from, the taxonomy of family management labour proposed by Reich-Stiebert et al. [2023], and what digital tools or technologies are used to support these discrete activities?

RQ2 Which domains of family management labour identified in this study align with, or diverge from, those proposed by Daminger [2022], and what digital tools or technologies are used to support them?

RQ3 How do participants’ experiences of the cognitive and emotional family management labour described by Robertson et al. [2019] surface needs, challenges, and opportunities for digital technologies that aim to support this work?

Method

Participants

We recruited 61 United Kingdom-based participants on Prolific using pre-screening to ensure diversity in household composition (mixed and same-sex couples, with and without children or informal caring roles) and socioeconomic background (education as proxy). Participants received £4.50 for a 30 minute survey. The study was approved by the university’s ethics committee.

Prior to analysis, we applied a single exclusion criterion: submissions that did not complete all survey sections were excluded. Eleven submissions met this criterion and were removed, yielding the final analytic sample of N = 50.

Participants ranged in age from 18 to 67 (median 39). Gender: 15 identified as male, 34 as female, 1 as non-binary. Thirty-two were cohabiting with a partner. Household compositions and management roles are reported in Tables 2 and 3.

Table 2: Household Characteristics

Table 3: Household Management Roles

Materials

The survey was built in REDCap for secure, GDPR compliant data capture. The survey comprised four parts: (1) Information sheet and consent; (2) Demographics; (3) Types of Cognitive Labour structured around Robertson et al. [2019]; and (4) Probes and visibility, using image-based informational probes to prompt reflection on otherwise abstract or hidden forms of labour.

Figure 1: This probe explains an example of the concept of monitoring using the example of tracking pets and tracking finances. Example materials generated by the authors using GPT-4.

Figure 2: Example of Survey section - Managerial Thinking probe and questions

Procedure

Participants followed a Prolific link to the REDCap survey. Demographics, including special category items, were collected first. Category questions were presented in random order to reduce order effects and fatigue. The survey took an average of 19 minutes (range 3 to 81).

Analysis and Results

We used a mixed-methods approach, combining inductive and deductive strategies. For RQ1 and RQ2, we conducted a structured content analysis using deductive category assignment [Mayring 2021]. For RQ3, we conducted a reflexive thematic analysis [Braun and Clarke 2006].

RQ1 Analysis

To address RQ1, we employed deductive content analysis, first openly coding participants’ accounts of family management labour, then systematically comparing codes with Reich-Stiebert et al.’s taxonomy of 44 labour terms [2023], using Mayring’s Structuring–Deductive Category Assignment approach [2021].

RQ1 Results

The content analysis reveals four key findings: (1) an established taxonomy of terms aligned with our data; (2) several novel terms extended current understanding; (3) established terms clustered around familiar domains such as Feeding and Care for Children; and (4) novel terms were linked to a scarcity of supporting digital tools.

Table 4: Taxonomy Data showing final taxonomy of terms from our data alongside the associated labours, domains and digital tools

Matched terms

Re-coded to Daminger terms

Re-coded to our terms

Novel terms from our data

Table 5: Terms not found in our data from Reich-Stiebert 2023 Taxonomy

From these results we highlight four insights:

1. Established Taxonomy of Cognitive Family Management: Many terms mapped directly or with minor recoding (rows 2–20), including Planning, Scheduling, Monitoring, Remembering, Assisting Others, Delegating, Coordinating, Organising, and Managing.
2. Uncharted Territories of Cognitive Work: Novel terms included Researching, Crowdsourcing, Ideation, Balancing Needs, Behaviour Management, Curating, Personalising, Advocating, Mediating, Empathising, and Soothing (self and others).
3. Established and Emerging Domains: Feeding and Care for Children were consistently strong domains with links to common tools. Novel domains such as Inclusion and Special Events were strongly associated with novel terms.
4. Conceptual Novelty and Tool Use: Novel activities were supported by fewer and less consistent tools.

RQ2 Analysis

To address RQ2, we used deductive category assignment content analysis [Mayring 2021], mapping participant domain-related codes to Daminger’s taxonomy [2022]. Daminger’s domains included Food, Care for Children, Logistics/Scheduling, Cleaning/Laundry, Shopping/Purchasing, Home/Car Maintenance, Travel/Leisure, Finances, Social Relationships.

RQ2 Results

Table 6: Domains from our data compared to Daminger [2022] and associated tools

Matched terms

Novel Terms

Terms not in our data

From this analysis, three findings emerged:

1. Emergence of Combined or Novel Domains: Inclusion, Special Events and Work-Life Balance did not appear in Daminger’s taxonomy but featured prominently in our dataset.
2. Disparities in Digital Support Across Domains: Domains linked to paid work (Finance, Logistics/Scheduling, Shopping/Purchasing) were associated with specific tools. In contrast, domains such as Feeding, Care for Children, and Social Relationships had less consistent tool reporting.
3. Tensions Between Sentiment and Tool Use: Finance attracted considerable negative sentiment yet had the most consistent tool use. Conversely, more positively described domains such as Feeding showed less consistent digital support.

RQ3 Analysis

To address RQ3, we conducted a reflexive thematic analysis [Braun and Clarke 2006], employing both inductive and deductive approaches. We coded labour experiences, digital tool use, and domains, then mapped codes onto a radar chart and iteratively refined themes through reflection on our positionality.

RQ3 Results

The analysis revealed six key themes.

Theme 1: Varied Enjoyment of Cognitive Labour

Participants had both positive and negative attitudes towards the deployment of labours. For some, these tasks brought enjoyment and satisfaction, while for others they felt burdensome or emotionally taxing. P13 noted, “I am really passionate when it comes to organisation and scheduling, I like being proactive.” P2 illustrated how routine cooking could serve as an act of care: “I am cooking one dish every weekend because it’s my partner’s favourite dish.”

Some participants resisted framing family management as inherently negative. P37 remarked, “it is a shared responsibility, so with two heads working together, the result is always amazing.” In contrast, when responsibility fell solely on one person, the experience tended to be more negative. P23 lamented, “This all falls on me. I plan all the meals, plan each child’s after school activities for the week, paying the children’s activities.”

Overall, there was no consistent link between technology use and enjoyment. Instead, participants’ feelings were shaped by context, domain, labour type, and household circumstances.

Theme 2: Relevance of Household Composition

Participants’ experiences of family management labour were significantly shaped by who they lived with and the relational dynamics of their households. Those living alone or without dependents often found that some labours were less relevant. As P5 noted, “I only have to consider myself so don’t need to worry about this too much.”

Among parents, the influence of household composition was especially pronounced, with child-rearing intensifying nearly all labour types. P8 described, “I am a single parent so I plan all events for myself and my child. Including regular activities, play dates, seeing friends and family.” P29 noted, “Making sure that our son who is ADHD follows a pattern on a daily basis otherwise he will freak out.”

Vision and values (originally theorised as metaparenting) emerged strongly, with parents setting boundaries, routines, and cultivating empathy. P3 noted: “Ensuring a consistent night-time routine is adhered to to support the development of a child in the house. Buying books and other materials to aid the learning of the child in the house.”

Theme 3: Feeding — The Intersection of Care, Inclusion, and Well-being

Feeding emerged as one of the most vivid and complex domains. Participants described aligning their food practices with ethical and environmental commitments: “I have values such as wanting to eat a predominantly vegetarian diet and using eco-friendly products in the home where possible” (P42). For others, shared meals were crucial to maintaining emotional connection: “I try to make time with my family to have a meal together” (P33).

Feeding also required personalising meals and coordinating with shifting household routines: “trying to juggle meals with food available, dietary preferences, people arriving unexpectedly, changing work locations, ability to get to the supermarket” (P36).

Despite this complexity, participants rarely used domain-specific tools. Instead, they turned to general-purpose technologies such as Google, social media, calendars, reminders, and notes.

Theme 4: Finance: A Recognised and Digitally Supported Domain

Managing household finances emerged as another vivid domain, closely linked to digital tools. P6 explained, “I am in control of the main bank account for the family and take responsibility for all bills and payments,” using “my banking app Monzo.” P13 noted, “finances is something I actually enjoy.” Others linked finance to broader values: “Ensuring that we’re smart with money at all times, never needing credit cards or getting into debt” (P44). Yet for some, money management was a source of stress: “I prefer don’t think about money.” (P2)

Financial labour stood out as the domain most consistently paired with digital tools.

Theme 5: Special and Sensitive Contexts

Participants described cognitive labour that emerges in non-routine, emotionally significant, or exceptional contexts—managing special events, fostering inclusion, and sustaining work-life balance.

Regarding special events, P21 detailed: “Buying for Christmas… presents, decorations, wrapping, posting, buying the Christmas tree and getting it home… ingredients needed for Christmas meals. Making the Christmas pudding/cake ahead of time.”

In terms of inclusion, P10 described: “Regulating my emotions from a hard day at work so as not to stress out my neurodivergent partner.”

The labour of work-life balance involved strategies such as separating work from personal time: “I separate my work life from my personal life” (P5).

These special and sensitive contexts appear to increase the need for specialist knowledge and skill even when the component tasks may appear routine.

Theme 6: Inclusion Through Everyday Self-Regulation

When asked about self-regulation, participants frequently described behaviours related to fostering inclusion within the household. Rather than enforcing individualistic self-regulation routines, this labour often involved managing one’s own actions to accommodate, soothe, or support others.

Empathising: “When I see that my partner has stress after work we usually go for a walk at our favourite places. We try to discuss the reasons for the stress and I support him as best as I can” (P2).

Assisting: “I have to take my partner to the toilet. I have to remind them to go to the toilet or they will soil themselves and stay in the mess without acknowledgement” (P15).

Reflecting: “I try to switch off from work, practise empathy and positive thinking, in order to create a happy home” (P43).

Maintaining Control: “I always try to act in a way that is homely to everyone in the household. One time I had to hide my anger and try correcting my daughter calmly over something terrible that she did” (P1).

Reminding: “My partner struggles to remember things and doesn’t seem to have any urgency… I also plan around how she is feeling” (P46).

Discussion

This study contributes to an emerging understanding of how digital tools intersect with the hidden labours of family management. We organise the discussion around four interrelated findings.

Digital Support for Meta-Labours

Our results indicate that some types of family management labour are more consistently supported by digital tools than others. Planning and Strategising, Monitoring and Anticipating Needs, and Knowing, Learning, and Remembering were often linked with a small but consistent set of tools. By contrast, Vision and Values (Metaparenting), Managerial Thinking, and Self-Regulation were associated with much lower and more fragmented levels of reported technology use.

This pattern suggests that support for meta-labours remains ad hoc and uneven, reliant on individual initiative rather than systematic technological provision. These more abstract and emotionally nuanced labours correspond to what Weeks and Ruppanner [2024] describe as “core” cognitive labours: ongoing, internal, and often invisible.

Design consideration: Interrogate the parts you can’t see. When designing for seemingly well-structured planning or monitoring tasks, designers should attend to the meta-labours embedded within them—particularly the values work, meaning-making, and anticipatory judgement that precede visible action.

Meaning-Making in Family Management

Some participants described aspects of family management labour as enjoyable or empowering, challenging the assumption that such labour is only a burden to be minimised. Enjoyment often arose when labour was visible, shared, or aligned with personal and household values.

Hybrid domains such as Feeding, Inclusion, Work-Life Balance, and Special Events were prominent sites of meaning-making. They combine routines, emotion, and culture, and were described as central and emotionally charged yet inconsistently supported by digital tools.

At the same time, technologies that promise convenience or satisfaction can reframe meaning in ways that entrench norms or increase workload. As Cowan [1983], Hackman [2023], and Strengers [2021] caution, framing domestic labour as “enjoyable” or “loving” can obscure that it remains unpaid and unequally distributed.

Design consideration: Automate the crappy parts. Digital tools often replace the most meaningful or relational aspects of family life, while leaving the least meaningful tasks such as laundry and repetitive preparation untouched. Designers might consider which aspects of labour families would actually prefer to delegate.

From Coordination to Collaboration: Rethinking Cooperation

We break down the concept of cooperation into coordination (allocating tasks, aligning schedules and information flows) and collaboration (co-authoring plans and norms, negotiating roles, and sharing accountability). Vision and Values and Self-Regulation are especially dependent on collaborative cooperation, but inconsistently supported by technology.

Participants’ responses also introduced descriptors for this labour—empathising and enforcing boundaries—that do not appear in Reich-Stiebert et al.’s taxonomy [2023], perhaps because they sit at the intersection of emotional and cognitive work.

Design consideration: Avoid accidental individualisation. Digital systems can inadvertently centralise domestic information and decision-making around a single family manager. Designers may consider how tools can support shared visibility, intentional collaboration, and consensual redistribution of context.

Family Crafting: Understanding the WHY of Domestic Labour

The most prominent emergent labour in our study was Vision and Values, termed Metaparenting by Robertson et al. [2019]. We broaden this to Life-Crafting to capture relevance beyond parenting—the work of making explicit the “why” that underpins everyday decisions. We propose this as a term that captures its multidimensional nature and links it to adjacent literatures such as Life-Crafting [van Zyl et al. 2023], Job Crafting [Mukherjee et al. 2023], and Conservation of Resources theory [Halbesleben et al. 2014].

Despite being richly articulated, participants rarely linked Life-Crafting to digital tools. Mentions were scattered across general-purpose platforms rather than consistent or purpose-built supports.

Life-Crafting spans activities such as planning, anticipating, decision-making, and reflection, often overlapping with other labour types. This distribution underlines its meta character: the “why” coordinates and anchors the “what.” Without it, work risks becoming fragmented and harder to delegate.

Design consideration: Understand and centralise the ‘why’ without automating it. Technologies are well suited to organising the how and the what of domestic action, but the why needs to be kept central and human rather than automated. Systems could help people to articulate, record and share the reasons that matter to them—a visible reference point for everyday decisions.

Limitations and Future Work

This study’s primary limitation was its reliance on a survey format. While this enabled a broad and diverse sample, it restricted our ability to probe how cognitive and emotional labours unfold in practice. We could not fully explore the situated use of technologies, their emotional impact, or the ways they support or complicate family work.

Because this was a one-time, self-reported survey, it cannot capture the more tacit, bodily, or evolving aspects of cognitive and emotional labour. Our claims therefore focus on participants’ reflective accounts rather than the full situated enactment of these practices.

Future work would benefit from qualitative and participatory approaches (e.g., interviews, diaries, ethnography, or co-design) that can surface pluralism, lived inequality, and contextual variation, particularly in relation to Life-Crafting and self-regulation. Future research could also explore how technologies might articulate and externalise family values in supportive rather than prescriptive ways.

Conclusion

This paper examined how digital technologies relate to six forms of family management labour and how participants describe enacting them. We found uneven support across these labours: participants reported that tools supported some activities (for example organising and monitoring) but left gaps elsewhere. Building on prior work, we surface Life-Crafting (household vision and values) and Self-Regulation as consequential yet weakly supported sites for research and innovation. We contribute a preliminary empirical mapping of digital support and gaps across these labours, and suggest directions for future research that explores how collaborative domestic technologies could make meta-labour visible, shareable, and negotiated across roles.

AI Assistance

The authors made limited use of AI tools for language editing, to resolve minor LaTeX formatting issues, and to generate illustrative example materials (e.g., image probes) used to demonstrate concepts. All substantive content, analysis, and arguments were developed by the authors.

Acknowledgements

We are grateful to the participants who generously shared their experiences of family management, and to friends and colleagues who offered feedback on early drafts. We also acknowledge all those who have carried hidden domestic labour in silence, as well as those who have worked to surface and contest it, including the scholars whose work has shaped and inspired this study. Finally, we are grateful for the work of the reviewers and associate committee chairs involved in peer review of this work.

Appendix A: Survey Structure and Coding Overview

Appendix B: Other Visual Probes

Figure 3: Visual probe illustrating the concept of knowing, learning, and remembering, using examples of everyday reminders and shared understandings of healthy balance. Example materials generated by the authors using GPT-4.

Figure 4: Visual probe illustrating the concept of managerial thinking using examples of a physical kanban style family organiser. Example materials generated by the authors using GPT-4.

Figure 5: Visual probe illustrating the concept of Planning and Strategising, using examples of dog training advice and an app for planning a family day out. Example materials generated by the authors using GPT-4.