From Polarization to ‘Cat Tax’: The Digital Noah’s Ark as Transient Refuge in the TikTok-RedNote Exodus

First Published Date: January 31st, 2025

Written by: Ahmet S. Sakrak, Bowen Zhang, Jiayi Zhu, Xinran Zhang, Xinyi Hu, Xinyi Wu

Introduction

Since the early days of Web 2.0, social media platforms have evolved into dynamic ecosystems where user-generated data, algorithmic content curation, and transnational connectivity shape the online experience (Helmond 2015; Ankerson 2010). Major platforms such as Facebook, Twitter, and — more recently — TikTok, exemplify how the platformization of the web has fostered continuous engagement, “collective intelligence,” and real-time interactivity (O’Reilly and Battelle 2009). Yet, alongside these affordances, platforms increasingly face governance pressures, data-privacy concerns, and geopolitical scrutiny, often sparking large-scale user migrations during crises (Newell et al. 2016). For instance, Twitter’s 2022 policy shifts under new leadership, marked by monetized features and reduced content moderation, drove disillusioned users to decentralized alternatives like Mastodon, which prioritized transparency and user autonomy (Jeong et al. 2024; La Cava et al. 2023). Similarly, peer influence and platform attractiveness have historically shaped voluntary migrations, such as the shift from Facebook to Instagram (Hou et al. 2020). However, the TikTokRefugees phenomenon introduces a distinct case: a geopolitical crisis compelling user to migrate not between Western platforms but to Xiaohongshu (RedNote), a Chinese lifestyle-centric app, where interactions defied expectations of polarization. In April 2024, President Biden signed legislation requiring ByteDance to divest TikTok’s U.S. operations by January 19, 2025, or face a national ban (CNN 2024). As the deadline loomed, a surge of American TikTok users — anticipating disruptions or disillusioned by data governance concerns — began migrating to RedNote by January 13, self-identifying as “TikTok Refugees” (BBC 2025a). Within days, RedNote topped the U.S. App Store’s free apps chart (BBC 2025b), its rise emblematic of a migration pattern diverging from prior studies. Unlike voluntary shifts between Western platforms (e.g., Twitter to Mastodon), this exodus was propelled by geopolitical coercion, algorithmic dissatisfaction, and socio-cultural curiosity. RedNote’s design, emphasizing lifestyle content, visual storytelling, and community-centric engagement, fostered an unexpectedly wholesome cross-cultural exchange. Users navigated linguistic barriers through hybrid “Chinglish” memes and rituals like “cat tax” (posting pet photos to build camaraderie), temporarily transcending the polarized discourse pervasive on platforms like TikTok. Yet, this optimism proved fragile. By the seventh day, governance contradictions — such as RedNote’s opaque censorship of politically sensitive terms — began eroding trust, mirroring the transient refuge of a “Digital Noah’s Ark” that shelters users from geopolitical storms but remains tethered to state-aligned infrastructures.

Against this backdrop, this study interrogates three core questions:

1. What geopolitical, algorithmic, and socio-cultural factors drove TikTok users to seek refuge in RedNote, and how did these motivations evolve during the first seven days of migration?

2. How did RedNote’s platform design and algorithmic curation facilitate wholesome cross-cultural interactions, and how did users negotiate barriers to sustain provisional solidarity?

3. Why did the initial optimism of this “Digital Noah’s Ark” fluctuates over time, and what does this suggest about the sustainability of crisis-driven digital havens?

By systematically examining this migration, the study extends scholarship on social media ecosystems (Jeong et al. 2023; Zia et al. 2023; Radivojevic et al. 2024), illustrating how platforms leverage “refuge” narratives amid governance failures while highlighting the precariousness of such havens. The findings suggest that cyclical migrations will recur where global crises intersect with Web 2.0 infrastructures, exposing the fragility of social media ecosystems shaped by algorithmic logic yet strained by 21st-century geopolitical fissures. Ultimately, this phenomenon challenges assumptions about online polarization, offering insights into how communities adapt — and how digital “arks” rise and fall — in an age of fragmented sovereignty.

Theoretical Framework

The theoretical underpinnings of this study are anchored in an integrative approach that bridges established theories of media consumption and migration with novel conceptualizations addressing the temporal and affective dynamics of crisis-driven platform shifts. This framework seeks to elucidate the motivations, adaptations, and networked behaviors of users navigating geopolitical disruptions, while critically engaging with the limitations of existing models.

Media Consumption and Migration Motivations

The Uses and Gratifications Theory (UGT) provides a foundational lens for understanding why individuals seek alternative digital spaces. Rooted in the premise that users actively select media to fulfill psychological and social needs (Katz et al. 1973), UGT contextualizes the migration from TikTok to RedNote as driven by desires for escapism (fleeing algorithmic polarization), social integration (rebuilding community in perceived safer spaces), and cognitive curiosity (exploring cross-cultural content). However, UGT’s focus on individual agency overlooks structural forces shaping platform ecosystems, necessitating complementary frameworks.

The Push-Pull-Mooring (PPM) model extends this analysis by categorizing migration drivers into push factors (e.g., dissatisfaction with TikTok’s governance and geopolitical instability), pull factors (e.g., RedNote’s lifestyle-centric design), and mooring factors (e.g., reduced switching costs under crisis conditions) (Bansal et al. 2005). While PPM effectively maps the initiation of migration, its static structure fails to account for the temporal volatility of user sentiment observed in this study’s seven-day corpus, where initial optimism gave way to governance-related skepticism.

Temporal-Affective Adaptation and Retention Dynamics

To address this gap, the Expectation-Confirmation Model (ECM) (Bhattacherjee 2001) is employed to analyze retention dynamics. ECM posits that user satisfaction hinges on the alignment between expectations and experiences. In this case, migrants entered RedNote with minimal expectations (“anywhere but TikTok”) but experienced positive confirmation through its communal rituals (e.g., “cat tax” traditions) and cross-cultural novelty. However, ECM’s linear logic — anticipating a stable satisfaction trajectory — proved inadequate as external shocks (e.g., censorship controversies) disrupted retention, underscoring the need for a temporally sensitive framework. This study also extended on the liminality of this phenomenon, a concept originated from Couldry and Hepp’s (2017) media ambivalence, to describe the transient phase where crisis, platform affordances, and user improvisation converge to create ephemeral solidarity. Platform liminality aims to capture how RedNote’s visual-centric design, optimized for apolitical content, temporarily suppressed ideological divides, fostering affective affinity among users. Yet, this liminal space proved fragile, destabilized by governance contradictions that mirrored the ecosystems users sought to escape. Thus, it has been aimed to emphasizing the provisional nature of digital utopias.

Networked Improvisation and Hybrid Communities

Granovetter’s (1973) strength of weak ties theory illuminates the provisional bonds formed during this migration, where users connected through niche interests (e.g., micro-celebrities, gaming) rather than ideological alignment. These weak ties facilitated cross-cultural curiosity but exemplified “thin solidarity,” unable to sustain engagement as governance flaws emerged. This phenomenon aligns with Wellman’s (2001) networked individualism, wherein digital platforms enable personalized, interestdriven networks that prioritize flexibility over depth.

Another idealism worth to be examined is to discover the platform’s transnationalism — a theory elaborated from Appadurai’s (1996) deterritorialization — to describe RedNote’s hybrid cultural spaces. Users navigated linguistic and governance barriers through tactical improvisation, blending English and Mandarin into “Chinglish” memes, thereby asserting agency within constrained infrastructures (de Certeau 1984). These practices reflect Papacharissi’s (2015) affective publics, where collective sentiment temporarily overrides structural critiques, yet also highlight the precariousness of such solidarity.

Methodology

Discourse Analysis

To examine the migration of “TikTok Refugees” to RedNote, this research adopts Reddit as a relatively neutral platform for discourse analysis, viewing language as a construct that shapes reality, reinforces power dynamics, and influences social institutions (Jones 2012). Following Jones’ argument that computer-assisted corpus analysis reveals discourse patterns and evolution (2012), we employ a mixed-method approach, integrating distant and close reading techniques. Distant reading involves large-scale computational analysis of Reddit data using Python, while close reading qualitatively examines key themes identified through network analysis, capturing the nuances of user comments.

Data Collection

Data was collected via PRAW (Python Reddit API Wrapper) for one week of Reddit comments (from 17 February backwards). Initially, 21,416 entries mentioning “RedNote” were extracted. This approach ensures legal and reliable data acquisition, although the final dataset omitted the search term “TikTokRefugees” due to insufficient volume for statistical significance.

Following Li et al. (2023), the data analysis proceeded through three main phases: data preprocessing, topic modeling, and sentiment analysis.

Data Preprocessing

Preprocessing employed NLTK (Natural Language Toolkit) for tokenization and stopwords filtering. We adapted standard NLTK stopwords to Reddit’s platform nuances. Specifically, we:

1. Removed or replaced emojis, user mentions, subreddit references (e.g., “r/Name”), Markdown syntax, and any extremely short comments.

2. Lowercased all text for consistency.

3. Expanded Reddit abbreviations (e.g., “AMA” to “ask me anything”) for clarity.

Topic Modeling

In this research, we used the LDA model to analyse the text in the dataset. To enhance topic coherence, we used the Mallet implementation of LDA, which applies Collapsed Gibbs Sampling and reportedly yields more accurate distributions than standard Gensim’s LDA (Papanikolaou et al. 2017). The C_V coherence score analysis (Figure: Coherence Score vs Number of Topics) guided our decision to divide the preprocessed data into 6 topics for further analysis.

For model implementation, the scikit-learn machine learning module (Pedregosa et al. 2011) trained the LDA model, and pyLDAvis (pyLDAvis developers 2025) helped visualize inter-topic distances and key terms.

Sentiment analysis Additionally, we utilized Python’s TextBlob module to perform sentiment analysis on the preprocessed data. TextBlob is a Python library designed for textual data processing, offering an easy-to-use API for performing various natural language processing (NLP) tasks (‘TextBlob: Simplified Text Processing — TextBlob 0.19.0 Documentation’). Meanwhile, we combined the results of sentiment analysis with the LDA model’s output to analyze Reddit users’ sentiments toward ‘TikTokRefugees’.

Data Analysis

Key Topics

Based on C_V coherence score results, the LDA model categorized the cleaned data into six topics. To visualize key terms, we produced:

• Word Clouds showing top five representative words per topic. (Figure: Word Clouds Per Topic)

• Bar Charts reflecting each topic’s proportion of the corpus. (Figure: Proportions of the Corpus Per Topic)

However, the key terms in each topic cannot tell a clear main theme for each topic. Thus, we conducted network analysis on the text data for each topic. We extracted top terms, computed average node scores, and reclassified topics accordingly, capturing the most representative comments. Based on the results derived from network analysis, the main themes of the six topics have been concluded.:

¨ Topic 0: “Deleted Comments.”

¨ Topic 1: “Language Barriers and Censorship Loopholes/Meme Culture.”

¨ Topic 2: “Regulatory Environment Differences.”

¨ Topic 3: “State Control over Digital Spaces.”

¨ Topic 4: “Unrestricted Global Communication & Cultural Exchange/Skepticism toward Government.”

¨ Topic 5: “Concerns about RedNote Censorship.”

As shown in the chart (Figure: Representative Clusters Per Topic), each topic has a clear borderline between themes. For example, Topic 5 reflects users’ anxiety about RedNote’s censorship. The highest-rated comment states:

“I think I’m going to have an aneurysm if that keeps bleeding out into other social media like TikTok censorship has been […] The censorship was the most nonsensical insanity ever […] You can’t even say the word ‘killed,’ you really have no business discussing true crime stories on this platform…”

Meanwhile, skepticism towards the governments and a desire for a digital utopia are expressed under Topic 4:

‘It’s really moments like this that makes you realize that there is a lot of bullshit about our respective governments that is designed to keep us from interacting with each other. We are all people of the world trying to have fun and get through this life and without barriers we could learn and have fun.’

Furthermore, Figure: Topic Frequency Over Time indicated that Topic 3 held the highest volume of discussion, whereas Topic 1 grew quickest, signifying heightened curiosity around Chinese social media and meme dynamics.

After being classified by the LDA model, the key discussion topics among Reddit users regarding the ‘TikTokRefugees’ in the seven days following its occurrence have been identified. In the next section, sentiment analysis through TextBlob will examine the emotional trends associated with these six topics, providing insights into why TikTok users turned to RedNote as an alternative platform.

Sentiment Analysis

We first examined how Reddit users’ overall sentiment toward ‘TikTokRefugees’ changed over the seven days. As illustrated in Figure: Hourly Sentiment Over Time with Trendline, the general sentiment remained largely positive, indicating that users initially responded favorably to discussions surrounding ‘TikTokRefugees’. However, two notable trends emerged: First, the sentiment score exhibited a gradual decline, suggesting that enthusiasm or positive perceptions may have waned as discussions progressed. Second, the hourly fluctuations in sentiment score within each day gradually decreased, indicating more stable reactions over time. While the topic initially sparked strong engagement, emotional intensity and discourse gradually tempered.

At the same time, by analyzing the normal distribution plots of sentiment scores across different topics discussed by Reddit users (Figure: Sentiment Score Distribution by Topic), we can observe that the distribution of sentiment scores is quite similar across all topics, regardless of the specific theme. However, it is worth noting that Topic 0 sustained a high volume of comments between 0 and 0.08 sentiment score. Additionally, Topic 1 and Topic 4 also stand out, exhibiting a substantially larger volume of comments than the other topics.

The sentiment score is presented per topic over time in Figure: Sentiment Score Over Time. As shown in the chart, Topic 0 and Topic 1 dominated discussions. Combined with the LDA model analysis above, it can be concluded that on Day 1 of the TikTokRefugees discussion, Reddit users were primarily focused on exploring an unfamiliar eastern culture. At the same time, they also expressed curiosity about RedNote’s censorship policies. For example, some users discovered that RedNote’s censorship system fails to recognize certain English keywords, allowing them to skip the platform’s moderation and post content that would otherwise be restricted:

“Funny thing is that their censorship does not work in English except for a few political keywords. You can’t say […] in Chinese on there but you can say the English translation \”fuck pussy\”.

Starting from Day 2, additional topics began to appear in Reddit users’ discussions. This downward trend, particularly in Topic 2, suggests that users’ initial enthusiasm gave way to uncertainty about TikTok Refugees’ long-term viability. As discussions evolved, concerns over state control (Topic 3 and 4) became more prominent, reinforcing a broader skepticism toward platform governance.

However, the decline in sentiment scores across topics came to an end at this point. From Day 3 onward, the sentiment scores of various topics began to fluctuate around a central value of 0.06, maintaining a relatively stable pattern. By the final day, sentiment scores in Topic 4 and Topic 5 rebounded, suggesting a shift from initial skepticism to cautious optimism. This evolution highlights how users navigate new digital landscapes — balancing policy concerns with aspirations for open dialogue and crosscultural exchange.

Discussion

The migration of TikTok users to RedNote (Xiaohongshu) during a seven-day event offers a unique opportunity to dissect how users navigate digital spaces under duress, revealing tensions between platform affordances, user agency, and pre-existing theories. By synthesizing distant reading (topic modeling, sentiment analysis) and close reading (discourse analysis).

Theoretical Reassessment: Bridging UGT, PPM, and ECM

a) Uses and Gratifications Theory (UGT): Beyond Passive Consumption

UGT posits that users actively select media to fulfill psychological or social needs (Katz et al. 1973). In the TikTok-to-RedNote migration, UGT explains why users sought alternatives: they desired escape from TikTok’s polarized environment and social integration in a calmer community. Close reading of comments like:

“I joined for the spite, but I am staying for the culture, and I’m really enjoying seeing how the Chinese live, seeing what a beautiful country it is, etc. Also, it’s refreshing to be around respectful intelligent people who know how to act right after deleting most of my American social media apps because I’m sick of the drama.”

This can be resonated with UGT’s emphasis on purposive media use. However, UGT alone cannot explain how users adapted to RedNote’s unfamiliar infrastructure or why satisfaction fluctuated over time.

b) Push-Pull-Mooring (PPM) Model: Geopolitics as a Structural Push

The PPM model traditionally categorizes migration drivers as push factors (e.g., dissatisfaction with TikTok’s ban), pull factors (e.g., RedNote’s lifestyle focus), and mooring factors (e.g., language barriers) (Bansal et al. 2005). While the model effectively maps the migration’s triggers — geopolitical bans as a push, RedNote’s design as a pull — it still requires more account on temporal dynamics. Distant reading showed sentiment peaks around Days 2 (novelty-driven optimism) and has relative downfalls by Day 7 (censorship concerns). Figure: Hourly Sentiment Score Over Time with Trendline

c) Expectation-Confirmation Model (ECM): Low Expectations, High Satisfaction

ECM can be addressed to explain why users stayed on RedNote despite governance flaws. Users migrated with minimal expectations (“anywhere but TikTok”), but RedNote’s communal warmth — embodied in “Cultural Exchange” and rituals like “cat tax” — exceeded their anticipations. As examples here noted in topic 4:

“A lot of us have actually found it refreshing to not talk about politics and just learn new things and hobbies and about the daily lives of people we’ve never really gotten to know. I’ve had no bad interactions everyone has been so nice but I also take the time to translate what I’m saying or commenting into Chinese, I’m really leaning a lot about Chinese culture and hope it doesn’t get ruined before the Chinese New Year.”

“It’s been oddly wholesome. Lots of learning both ways. Like asking each other what high school is like there, exchanging memes, lots of “cat tax” posts (where they demand foreigners must post pictures of their cats as a tax for showing up on the app).” This resonates with Bhattacherjee’s (2001) idea that satisfaction hinges on the gap between expectations and experience. However, ECM’s linear logic (expectation → confirmation → satisfaction) falters when external forces (e.g., censorship) disrupt the cycle, as seen in this example within topic 5:

“xhs basically shadow bans anything remotely touching politics… unless it’s a praise of the Chinese system”

Algorithmic Liminality: Transient Utopias in Platform Interstices

The phenomenon of the emerging in algorithmic liminal space where crisis, platform affordances, and user improvisation converge to create ephemeral solidarity, is extended from Couldry and Hepp’s (2017) media ambivalence, aim to emphasizing how users tactically exploit platform infrastructures during disruptions.

Mechanisms of Liminality

• Temporal Compression: The short timeframe amplified users’ willingness to suspend skepticism. Distant reading showed sentiment scores peaked on Day 2, with users expressing surprise at RedNote’s positivity:

“I joined yesterday (I’m in Australia) and shared some pictures/videos of my cat. Everyone’s super nice and sharing their own cat pictures + sending my cat compliments in broken English. It’s weirdly wholesome and I like it. Also seen some of the Chinese userbase responding to Family Guy and Modern Family videos with confusion, fascination and interest. I give it 4 weeks until the Americans ruin it.”

• Affective Affinity Over Ideology: “Meme Culture” (can be found in topic 1) comments revealed how users bonded through hybrid language (e.g., “Chinglish” captions) and shared interests (micro-celebrities, gaming), sidestepping geopolitical divides. This aligns with Jenkins’ (2006) participatory culture, where communal play fosters provisional belonging.

• Algorithmic Amplification: RedNote’s recommendation algorithms, optimized for visual and lifestyle content, surfaced apolitical posts (e.g., pet photos, recipes), creating a feedback loop of positivity. This contrasts with TikTok’s engagement-driven curation of divisive content (Chen et al. 2022).

Liminality’s Fragility

By Day 7, sentiment fluctuates in topic 0 as users encountered governance contradictions (Figure: Sentiment Score Over Time). A comment lamented:

“No Tiananmen, Taiwan, Hong Kong, Tibet, Uyghur, Pooh Bear, military, CCP, or social credit talk at all…at least no talk that doesn’t tow the bottom line of the CCP.”

This mirrors Papacharissi’s (2015) affective publics, where collective euphoria is transient, giving way to disillusionment as structural realities resurface.

Networked Individualism and the “Thin Solidarity” of Weak Ties

The migration exemplifies Wellman’s (2001) networked individualism, where digital platforms enable personalized, interestdriven networks. However, cross-cultural ties remained shallow, reflecting Granovetter’s (1973) “strength of weak ties”: users connected through niche affinities (e.g., Taylor Swift fandom) but lacked deeper relational investment.

Case in Point: Hybrid Communities

Weak-Tie Serendipity: A user described bonding with a Shanghai-based RedNote user over Chinese online cultural trend like internet celebrities and gaming, leading to DMs about more of such conversations. This connection, while meaningful, relied on shared consumption rather than ideological alignment:

“From “TikTok refugees” lingering on Chinese social media, to “China Travel” becoming a global trend; from Li Ziqi’s emotional return that moved her overseas fans, to the Chinese video game Black Myth: Wukong introducing more people to Chinese culture — what makes China so magnetic and compelling today? Undoubtedly, it stems from China’s profound historical and cultural heritage, its ever-evolving modern outlook, its openness, the friendliness of its people, and the inclusivity of its society.”

Platformed Proximity: RedNote’s design compressed users from polarized ecosystems into a shared space, forcing accidental encounters. Network theory frames this as information cascades (Watts 2002), where early adopters’ posts (e.g., “How to bypass RedNote’s sign-up”) incentivized others to migrate:

“There are already a lot of step-by-step guides on TikTok showing people how to do it. Also, they’re apparently getting overwhelmed by signups which is slowing the servers to the point that it’s taking a while for people to get verification codes”

While weak ties fostered cross-cultural curiosity, they proved inadequate to sustain long-term engagement. As sentiment scores stablized (Days 4–6) Figure: Sentiment Score Over Time, users reverted to familiar behaviors: Topic 4 discussions fragmented into subcommunities (e.g., “working culture”), as Sunstein’s (2017) echo chamber paradox resonating.

Why This Matters: A Counter-Narrative to Digital Polarization

The seven-day “wholesome interlude” challenges deterministic narratives of inevitable polarization. Three implications emerge:

a) Platform Affordances Shape Discursive Possibilities

RedNote’s visual-centric, apolitical design temporarily suppressed conflict, proving that platform architectures can — if unintentionally — foster positivity. This contradicts Benkler et al.’s (2018) network propaganda, which posits that algorithms inherently amplify division.

b) Crisis as a Catalyst for Improvisation

The migration underscores users’ capacity to repurpose platforms during crises. Memes like “TikTok Refugee” weaponized humor to transform geopolitical alienation into communal identity, resonating with boyd’s (2010) concept of networked publics.

c) The Ephemerality of Digital Utopias

The corpus captures a fleeting equilibrium where algorithmic serendipity and user creativity aligned. Yet, RedNote’s governance under regional laws and censorship flaws ultimately mirrored the ecosystems users fled, underscoring Gillespie’s (2018) argument that platforms balance idealism with operational realities, thus reveals the actual “digital Noah’s ark” is merely an metaphor to escape the temporal extremism. In an era of escalating platform wars, these lessons remind us that even fractured media ecologies hold pockets of connection — however fleeting.

Conclusion

The migration of TikTok users to RedNote (Xiaohongshu) in response to geopolitical pressures offers critical insights into the interplay of platform governance, user agency, and cross-cultural solidarity in an era of fragmented digital sovereignty. This study, grounded in computational methods (LDA topic modeling, sentiment analysis) and critical discourse analysis, reveals that crisis-driven platform migrations are not merely reactive but generative, fostering ephemeral spaces of interaction that challenge assumptions about online polarization.

First, the motivations behind this exodus — geopolitical coercion, algorithmic dissatisfaction, and socio-cultural curiosity — underscore the complex push-pull dynamics shaping user behavior. While the Push-Pull-Mooring (PPM) model and Uses and Gratifications Theory (UGT) explain the migration’s initiation, the Expectation-Confirmation Model (ECM) and the concept of algorithmic liminality illuminate its transient cohesion. Users’ initial optimism, fueled by RedNote’s “lifestyle-first” design and rituals like “cat tax,” gave way to skepticism as governance contradictions (e.g., censorship of politically sensitive terms) eroded trust. This trajectory mirrors the metaphor of a Digital Noah’s Ark, where refuge from geopolitical storms proves precarious, tethered to the very infrastructures users sought to escape.

Second, the study highlights how platform affordances — such as RedNote’s visual-centric interface and apolitical algorithmic curation — temporarily suppressed polarization, enabling cross-cultural exchanges that defied mainstream narratives of U.S.-China antagonism. Hybrid practices like “Chinglish” memes and weak-tie networks around niche interests exemplified platformed transnationalism, where users navigated linguistic and cultural barriers through tactical improvisation. Yet, these interactions remained fragile, sustained more by novelty and crisis urgency than durable infrastructural support.

Finally, the findings challenge deterministic narratives of algorithmic polarization, suggesting that platform architectures can — intentionally or not — foster provisional solidarity. However, this solidarity is inherently unstable, as governance asymmetries and data-colonial logics resurface. The TikTok-to-RedNote migration thus epitomizes the paradox of digital havens: they emerge as sites of resistance yet remain bound to the geopolitical and economic systems they critique.

Appendix

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