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Pika: Empowering Non-Programmers to Author Executable Governance Policies in Online Communities

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Paper breakdownThe authors' claims, conditions and measurements, as JSON Signed receiptProof this review has not been altered
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Leijie Wang, Nicolas Vincent, Julija Rukanskaitė, Amy X. Zhang

Human-Computer Interaction · Submitted 6 Oct 2023

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim Our user studies with 17 participants show that Pika can empower non-programmers to author governance policies approximately 2.5 times faster than programmers who author in code.

how it is stated · asserted 0.95 read the record →

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arXiv ID2310.04329 (version 2)
Pith IDVF623W5I, Pith's permanent record of this paper and its review
CitationAmy X. Zhang, Julija Rukanskait\.e, Leijie Wang, Nicolas Vincent. "Pika: Empowering Non-Programmers to Author Executable Governance Policies in Online Communities." arXiv:2310.04329 (2023). https://pith.science/paper/VF623W5I
Claim paper

The compiled record

The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 5,547 input tokens.

What the abstract itself states, as probabilities: claims first 0.06 · states limitation 0.16 · human participants 0.97 · controlled comparison 0.78 · randomized assignment 0.02 · states quantitative result 0.99 · compares with prior results 0.81 · mentions code or data availability 0.05.

The abstract, sentence by sentence

arXiv listing abstract v2. Results and the main claim are underlined; .

Internet users have formed a wide array of online communities with nuanced and diverse community goals and norms. However, most online platforms only offer a limited set of governance models in their software infrastructure and leave little room for customization. Consequently, technical proficiency becomes a prerequisite for online communities to build governance policies in code, excluding non-programmers from participation in designing community governance. In this paper, we present Pika, a system that empowers non-programmers to author a wide range of executable governance policies. At its core, Pika incorporates a declarative language that decomposes governance policies into modular components, thereby facilitating expressive policy authoring through a user-friendly, form-based web interface. Our user studies with 17 participants show that Pika can empower non-programmers to author governance policies approximately 2.5 times faster than programmers who author in code. We also provide insights about Pika's expressivity in supporting diverse policies that online communities want.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#sentencerolethe authors' own workstates the main conclusionstrength
s0 Internet users have formed a wide array of online communities with nuanced and diverse community goals and norms. background 1.00 0.05 0.02 asserted 1.00
s1 However, most online platforms only offer a limited set of governance models in their software infrastructure and leave little room for customization. background 0.75 0.07 0.02 asserted 1.00
s2 Consequently, technical proficiency becomes a prerequisite for online communities to build governance policies in code, excluding non-programmers from participation in designing community governance. background 0.73 0.05 0.04 asserted 1.00
s3 In this paper, we present Pika, a system that empowers non-programmers to author a wide range of executable governance policies. contribution 1.00 0.87 0.42 asserted 1.00
s4 At its core, Pika incorporates a declarative language that decomposes governance policies into modular components, thereby facilitating expressive policy authoring through a user-friendly, form-based web interface. method 0.97 0.81 0.09 asserted 1.00
s5 Our user studies with 17 participants show that Pika can empower non-programmers to author governance policies approximately 2.5 times faster than programmers who author in code. result 1.00 0.97 0.35 asserted 0.95
s6 We also provide insights about Pika's expressivity in supporting diverse policies that online communities want. contribution 0.66 0.90 0.07 asserted 0.91

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from observation or experiment 1.00.

What was examined, and what was not

sources read
  • arXiv listing abstract v2
not examined
  • full text
  • figures and tables
  • references and citing sentences
  • relations to other papers
levels run
  • P abstract
not run
  • S sections
  • T body sentences
  • C citations
  • R cross-paper relations

Every quoted sentence on this record is the authors'. Every label is from Pith's closed vocabulary, with the probability shown beside it. Every number in the measurements table is the authors', checked by code. Record as JSON

The paper
Original abstract

Internet users have formed a wide array of online communities with nuanced and diverse community goals and norms. However, most online platforms only offer a limited set of governance models in their software infrastructure and leave little room for customization. Consequently, technical proficiency becomes a prerequisite for online communities to build governance policies in code, excluding non-programmers from participation in designing community governance. In this paper, we present Pika, a system that empowers non-programmers to author a wide range of executable governance policies. At its core, Pika incorporates a declarative language that decomposes governance policies into modular components, thereby facilitating expressive policy authoring through a user-friendly, form-based web interface. Our user studies with 17 participants show that Pika can empower non-programmers to author governance policies approximately 2.5 times faster than programmers who author in code. We also provide insights about Pika's expressivity in supporting diverse policies that online communities want.

Human review

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How the literature uses it

2 arXiv papers cite this in 4 sentences

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

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