A view that permits a GET to allow listing all the entries
in the database

**Route** - `/entries`

#Query Parameters -

- `?search=` - Search by title, description, get_involved, interest,
creator, and tag.
- `?ids=` - Filter only for entries with specific ids. Argument
must be a comma-separated list of integer ids.
- `?tag=` - Allows filtering entries by a specific tag
- `?issue=` - Allows filtering entries by a specific issue
- `?help_type=` - Allows filtering entries by a specific help type
- `?has_help_types=<True or False>` - Filter entries by whether they have
help types or not. Note that `True`
or `False` is case-sensitive.
- `?featured=True` (or False) - both capitalied. Boolean is set in admin UI
- `?page=` - Page number, defaults to 1
- `?page_size=` - Number of results on a page. Defaults to 48
- `?ordering=` - Property you'd like to order the results by. Prepend with
`-` to reverse. e.g. `?ordering=-title`
- `?moderationstate=` - Filter results to only show the indicated moderation
state, by name. This will only filter if the calling
user has moderation permissions.

GET /api/pulse/v2/entries/?ordering=published_by__profile&page=36
HTTP 200 OK
Allow: GET, POST, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "count": 1836,
    "next": "https://api.mozillapulse.org/api/pulse/v2/entries/?ordering=published_by__profile&page=37",
    "previous": "https://api.mozillapulse.org/api/pulse/v2/entries/?ordering=published_by__profile&page=35",
    "results": [
        {
            "id": 2537,
            "content_url": "https://posmo.coop/",
            "is_bookmarked": false,
            "tags": [
                "data",
                "data futures lab",
                "data governance",
                "data stewardship"
            ],
            "issues": [
                "Decentralization",
                "Openness"
            ],
            "help_types": [],
            "published_by": "Shandukani Mulaudzi",
            "submitter_profile_id": 5750,
            "bookmark_count": 0,
            "related_creators": [
                {
                    "name": "POSMO",
                    "profile_id": 6342,
                    "is_active": false
                }
            ],
            "entry_type": "base",
            "title": "POSMO",
            "description": "Posmo is a data cooperative based in Zurich, Switzerland working on ethical ways of collecting and creating value from mobility data. Posmo will continue to develop the Posmo Data Market, a trustworthy data space offering detailed personal mobility and socioeconomic data to third parties while providing data subjects with control over the use of their data. This year, among other milestones, Posmo will continue to develop its data governance processes, define a set of criteria for sharing mobility data with third parties, and build the internal approval process through the ethics committee.",
            "get_involved": "",
            "get_involved_url": "",
            "interest": "",
            "featured": false,
            "published_by_creator": false,
            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2023-05-16_092510.3997720000.png",
            "created": "2023-05-16T09:25:10.399300Z",
            "moderation_state": 3
        },
        {
            "id": 2538,
            "content_url": "https://tattle.co.in/",
            "is_bookmarked": false,
            "tags": [
                "data",
                "data futures lab",
                "data stewardship"
            ],
            "issues": [
                "Digital Inclusion"
            ],
            "help_types": [],
            "published_by": "Shandukani Mulaudzi",
            "submitter_profile_id": 5750,
            "bookmark_count": 0,
            "related_creators": [
                {
                    "name": "Tattle",
                    "profile_id": 6343,
                    "is_active": false
                }
            ],
            "entry_type": "base",
            "title": "Tattle",
            "description": "Tattle is a civic technology company working for a healthier online information ecosystem in India. They will continue to develop Uli, their browser plugin that gives social media users tools for a collective response to online gender-based violence, and seek to include new crowdsourcing tools for annotation and reporting.",
            "get_involved": "",
            "get_involved_url": "",
            "interest": "",
            "featured": false,
            "published_by_creator": false,
            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2023-05-16_092752.2949590000.png",
            "created": "2023-05-16T09:27:52.294736Z",
            "moderation_state": 3
        },
        {
            "id": 2539,
            "content_url": "https://www.tidepool.org/",
            "is_bookmarked": false,
            "tags": [
                "big data",
                "data",
                "data donation",
                "data futures lab",
                "data stewardship"
            ],
            "issues": [
                "Openness"
            ],
            "help_types": [],
            "published_by": "Shandukani Mulaudzi",
            "submitter_profile_id": 5750,
            "bookmark_count": 0,
            "related_creators": [
                {
                    "name": "Tidepool",
                    "profile_id": 6344,
                    "is_active": false
                }
            ],
            "entry_type": "base",
            "title": "Tidepool",
            "description": "Tidepool is a nonprofit organization based in San Francisco, California, developing technology to provide intuitive software products that help people with diabetes. Tidepool will continue to grow its Big Data Donation Project, which enables people to donate data from their diabetes devices to help fuel the next generation of diabetes research. During this year, they will develop a blanket real-world evidence protocol to expand the potential impact of the donated data. They will also conduct interviews to develop a report to help measure and share the impact of the data sets donated to date.",
            "get_involved": "",
            "get_involved_url": "",
            "interest": "",
            "featured": false,
            "published_by_creator": false,
            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2023-05-16_093635.6820400000.jpg",
            "created": "2023-05-16T09:36:35.681857Z",
            "moderation_state": 3
        },
        {
            "id": 2439,
            "content_url": "https://www.deepreckonings.com/",
            "is_bookmarked": false,
            "tags": [
                "AI",
                "algorithms",
                "cma",
                "cma2019",
                "creative media awards",
                "mozilla-cma"
            ],
            "issues": [
                "Web Literacy",
                "Privacy & Security"
            ],
            "help_types": [],
            "published_by": "Shandukani Mulaudzi",
            "submitter_profile_id": 5750,
            "bookmark_count": 0,
            "related_creators": [
                {
                    "name": "Stephanie Lepp",
                    "profile_id": 6058,
                    "is_active": false
                }
            ],
            "entry_type": "base",
            "title": "Deep Reckonings",
            "description": "This project uses deepfakes to address the issue of deepfakes. Three false videos will show public figures — like tech executives — reckoning with the dangers of synthetic media. Each video will be clearly watermarked and labeled as a deepfake to prevent misinformation.",
            "get_involved": "",
            "get_involved_url": "",
            "interest": "",
            "featured": false,
            "published_by_creator": false,
            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2022-11-08_094546.2259840000.png",
            "created": "2022-11-08T09:45:46.225693Z",
            "moderation_state": 3
        },
        {
            "id": 2440,
            "content_url": "https://moondisaster.org/",
            "is_bookmarked": false,
            "tags": [
                "AI",
                "artificial intelligence",
                "cma",
                "cma2019",
                "creative media awards",
                "deepfake",
                "disinformation",
                "fake news",
                "mozilla-cma"
            ],
            "issues": [
                "Web Literacy",
                "Privacy & Security"
            ],
            "help_types": [
                "Promote",
                "Test & feedback",
                "Watch session"
            ],
            "published_by": "Shandukani Mulaudzi",
            "submitter_profile_id": 5750,
            "bookmark_count": 0,
            "related_creators": [
                {
                    "name": "Halsey Burgund",
                    "profile_id": 6059,
                    "is_active": false
                },
                {
                    "name": "Francesca Panetta",
                    "profile_id": 6060,
                    "is_active": false
                },
                {
                    "name": "Magnus Bjerg Mortensen",
                    "profile_id": 6061,
                    "is_active": false
                },
                {
                    "name": "Jeff DelViscio",
                    "profile_id": 6062,
                    "is_active": false
                },
                {
                    "name": "MIT Center for Advanced Virtuality",
                    "profile_id": 6063,
                    "is_active": false
                }
            ],
            "entry_type": "base",
            "title": "In Event of Moon Disaster",
            "description": "This project uses the 1969 moon landing to explore the topic of modern misinformation. Real coverage of the landing will be presented on a website alongside deepfakes and other false content, to highlight the difficulty of telling the two apart. And by tracking viewers’ attention, the project will reveal which content captivated viewers more.",
            "get_involved": "",
            "get_involved_url": "",
            "interest": "",
            "featured": false,
            "published_by_creator": false,
            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2022-11-08_113014.8539260000.jpg",
            "created": "2022-11-08T11:30:14.853643Z",
            "moderation_state": 3
        },
        {
            "id": 2441,
            "content_url": "https://facework.app/",
            "is_bookmarked": false,
            "tags": [
                "AI",
                "algorithmic bias",
                "bias",
                "cma",
                "cma2019",
                "creative media awards",
                "facial recognition",
                "mozilla-cma"
            ],
            "issues": [
                "Web Literacy",
                "Digital Inclusion"
            ],
            "help_types": [],
            "published_by": "Shandukani Mulaudzi",
            "submitter_profile_id": 5750,
            "bookmark_count": 0,
            "related_creators": [
                {
                    "name": "Kyle McDonald",
                    "profile_id": 6064,
                    "is_active": false
                }
            ],
            "entry_type": "base",
            "title": "Most FACE Ever [Facework]",
            "description": "This project teaches users about computer vision and facial analysis technology through playful challenges. Users will enable their webcam, engage with facial analysis, and try to “look” a certain way — say, “criminal,” or “white.” The game reveals how inaccurate and biased facial analysis can often be.",
            "get_involved": "",
            "get_involved_url": "https://facework.app/",
            "interest": "",
            "featured": false,
            "published_by_creator": false,
            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2022-11-08_121249.9904940000.png",
            "created": "2022-11-08T12:12:49.990015Z",
            "moderation_state": 3
        },
        {
            "id": 2528,
            "content_url": "https://incidentdatabase.ai/",
            "is_bookmarked": false,
            "tags": [
                "audit tools",
                "mozilla",
                "mozilla-mtf",
                "mozilla technology fund"
            ],
            "issues": [
                "Openness"
            ],
            "help_types": [],
            "published_by": "Shandukani Mulaudzi",
            "submitter_profile_id": 5750,
            "bookmark_count": 0,
            "related_creators": [
                {
                    "name": "Responsible AI Collaborative",
                    "profile_id": 6331,
                    "is_active": false
                }
            ],
            "entry_type": "base",
            "title": "AI Risk Checklists",
            "description": "A common approach across all risk audit processes is risk identification. Once risks are identified, auditors determine their probability and impacts. While several firms dedicated to the audit of AI have built their own risk check listing artifacts, commercial checklists are considered proprietary and confidential. In short, there is an incipient closing of the core processes and technologies backing AI audits. Their plan to enable open-source AI risk check listing is to build on top of the code, data, and metadata of their collaborative open-source project the AI Incident Database.",
            "get_involved": "",
            "get_involved_url": "",
            "interest": "",
            "featured": false,
            "published_by_creator": false,
            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2023-05-10_100652.8987480000.jpg",
            "created": "2023-05-10T10:06:52.898515Z",
            "moderation_state": 3
        },
        {
            "id": 2529,
            "content_url": "https://github.com/EleutherAI/lm-evaluation-harness",
            "is_bookmarked": false,
            "tags": [
                "audit tools",
                "mozilla",
                "mozilla technology fund",
                "mtf"
            ],
            "issues": [
                "Openness"
            ],
            "help_types": [],
            "published_by": "Shandukani Mulaudzi",
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            "related_creators": [
                {
                    "name": "Big Science",
                    "profile_id": 6332,
                    "is_active": false
                }
            ],
            "entry_type": "base",
            "title": "Evaluation Harness",
            "description": "Evaluation Harness is an open-source tool for the evaluation of large language models. The framework defines a flexible API for both model and evaluation implementation and handles all of the work to orchestrate evaluations internally. Historically, the team has used prior datasets and proposed prompts for 0-shot and few-shot evaluation of language models. Their current project focus is to provide additional datasets with human judgments for summarization in multiple languages, to allow richer evaluation of multilingual language models.",
            "get_involved": "",
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            "interest": "",
            "featured": false,
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            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2023-05-10_101028.2720700000.jpg",
            "created": "2023-05-10T10:10:28.271829Z",
            "moderation_state": 3
        },
        {
            "id": 2530,
            "content_url": "https://crossover.social/",
            "is_bookmarked": false,
            "tags": [
                "#",
                "audit tools",
                "mozilla-mtf",
                "mozilla technology fund"
            ],
            "issues": [
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            "help_types": [],
            "published_by": "Shandukani Mulaudzi",
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                {
                    "name": "Check First",
                    "profile_id": 6333,
                    "is_active": false
                }
            ],
            "entry_type": "base",
            "title": "CrossOver",
            "description": "CrossOver simulates social media and big platform users to collect data about recommended content and then compares it to data provided by the platform's own APIs when available. Its monitoring devices are hosted by volunteers at residential addresses. Monitored websites are Twitter, YouTube, Facebook pages and groups, Google search predictions, Google News, Reddit, Odysee, and Mastodon. Building on top of their pilot project in Belgium, they will add 14 monitoring devices to seven French-speaking countries around the world.",
            "get_involved": "",
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            "interest": "",
            "featured": false,
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            "created": "2023-05-10T10:18:08.310319Z",
            "moderation_state": 3
        },
        {
            "id": 2531,
            "content_url": "https://docs.tracking.exposed/guardoni/guardoni-intro/",
            "is_bookmarked": false,
            "tags": [
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                "mozilla-mtf",
                "mozilla technology fund"
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            "issues": [
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            "help_types": [],
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                {
                    "name": "Algorithms Exposed",
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            ],
            "entry_type": "base",
            "title": "AI Forensics",
            "description": "AI Forensics is building a free-software toolkit to make investigations on TikTok and YouTube's recommendation engine accessible to a wider and more diverse community of researchers. The team has been pioneering methodologies to investigate social media recommender systems for more than seven years. They have developed various tools to support this research. The goal of this project is to make these tools more accessible, in order to increase the audit capacity of the research community, and hold platforms more accountable to their users and to the law.",
            "get_involved": "",
            "get_involved_url": "",
            "interest": "",
            "featured": false,
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            "created": "2023-05-10T10:30:39.572083Z",
            "moderation_state": 3
        },
        {
            "id": 2532,
            "content_url": "https://gigbox.media.mit.edu/",
            "is_bookmarked": false,
            "tags": [
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                "mozilla",
                "mozilla-mtf",
                "mozilla technology fund"
            ],
            "issues": [
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            "help_types": [],
            "published_by": "Shandukani Mulaudzi",
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                {
                    "name": "The Workers’ Algorithm Observatory (WAO)",
                    "profile_id": 6335,
                    "is_active": false
                }
            ],
            "entry_type": "base",
            "title": "Gigbox",
            "description": "The Workers’ Algorithm Observatory (WAO) is a crowdsourced auditing collaboration for investigating black-box systems in the platform economy. Investigations of platform economy algorithms, such as those used by Uber and DoorDash, face major challenges in accessing the data necessary for a meaningful audit. To solve this, the team behind WAO is developing an algorithm observatory for workers and allies to audit the black-box algorithms behind platforms through crowdsourced data collection among peers.",
            "get_involved": "",
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            "interest": "",
            "featured": false,
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            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2023-05-10_103241.8078300000.png",
            "created": "2023-05-10T10:32:41.807623Z",
            "moderation_state": 3
        },
        {
            "id": 2534,
            "content_url": "https://wonyoung.so/",
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            "tags": [
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            ],
            "issues": [],
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            "published_by": "Shandukani Mulaudzi",
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                {
                    "name": "Wonyoung So",
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            ],
            "entry_type": "base",
            "title": "Countering Tenant Screening",
            "description": "Countering Tenant Screening Using Tenant Screening Data aims to develop a crowdsourcing tool and/or campaign to audit tenant screening services used by property owners. It seeks to reveal the patterns of the inner algorithms, data structures, and representations, by collecting tenant screening reports as well as denied renters’ experiences.",
            "get_involved": "",
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            "interest": "",
            "featured": false,
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            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2023-05-10_103619.0422370000.jpg",
            "created": "2023-05-10T10:36:19.041970Z",
            "moderation_state": 3
        },
        {
            "id": 2536,
            "content_url": "https://ooni.org/",
            "is_bookmarked": false,
            "tags": [
                "censorship",
                "data",
                "data futures lab",
                "open source"
            ],
            "issues": [
                "Decentralization",
                "Openness"
            ],
            "help_types": [],
            "published_by": "Shandukani Mulaudzi",
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            "related_creators": [
                {
                    "name": "Open Observatory of Network Interference",
                    "profile_id": 6341,
                    "is_active": false
                }
            ],
            "entry_type": "base",
            "title": "Open Observatory of Network Interference (OONI)",
            "description": "OONI is a global free software project measuring internet censorship around the world. Since 2012, OONI has openly published more than a billion network measurements from 241 countries and territories, thereby hosting one the largest open datasets on internet censorship to date. They will develop a new version of OONI Run, a tool that allows coordinated testing of website blocking using OONI's existing infrastructure and contributing to its dataset. They seek to deploy this tool in the field through their established partnerships with 41 digital rights organizations around the world.",
            "get_involved": "",
            "get_involved_url": "",
            "interest": "",
            "featured": false,
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            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2023-05-16_081703.5505250000.png",
            "created": "2023-05-16T08:17:03.550315Z",
            "moderation_state": 3
        },
        {
            "id": 2442,
            "content_url": "https://www.futurewake.com/#/",
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            "tags": [
                "AI",
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                "cma",
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                "mozilla-cma",
                "predictive policing"
            ],
            "issues": [
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                "Digital Inclusion"
            ],
            "help_types": [],
            "published_by": "Shandukani Mulaudzi",
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            "related_creators": [
                {
                    "name": "Future Wake",
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                }
            ],
            "entry_type": "base",
            "title": "Future Wake",
            "description": "This interactive web app turns the discriminatory practice of predictive policing upside down, instead allowing citizens to predict police brutality. The project uses AI and a number of data sets to determine where, when, and how police brutality in the U.S. is most likely to occur. It also paints a vivid picture of the potential victim, from their skin color to their age, to put a human face on the prediction.",
            "get_involved": "",
            "get_involved_url": "https://www.futurewake.com/#/",
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            "featured": false,
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            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2022-11-08_123949.2507820000.png",
            "created": "2022-11-08T12:39:49.250559Z",
            "moderation_state": 3
        },
        {
            "id": 2443,
            "content_url": "https://www.afroalgorithms.com/",
            "is_bookmarked": false,
            "tags": [
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                "AI",
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                "algorithmic bias",
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                "creative media awards",
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            ],
            "issues": [],
            "help_types": [],
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            "related_creators": [
                {
                    "name": "Anatola Araba",
                    "profile_id": 6066,
                    "is_active": false
                }
            ],
            "entry_type": "base",
            "title": "Afro Algorithms",
            "description": "This 3D animated short film in the Afrofuturist genre explores the topics of AI and bias. In a distant future, an artificial intelligence named Aero is inaugurated as the world’s first AI ruler. But Aero soon learns that important worldviews are missing from her databank, including the experiences of the historically marginalized and oppressed. A slate of well-known Black artists lend their voices to the film, including Robin Quivers, Hoji Fortuna, and Ava Raiin.",
            "get_involved": "",
            "get_involved_url": "https://www.afroalgorithms.com/",
            "interest": "",
            "featured": false,
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            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2022-11-08_130305.5146410000.png",
            "created": "2022-11-08T13:03:05.514417Z",
            "moderation_state": 3
        },
        {
            "id": 2444,
            "content_url": "http://www.hopeimmersive.com/",
            "is_bookmarked": false,
            "tags": [
                "AI",
                "AI bias",
                "algorithmic bias",
                "algorithmic racism",
                "cma",
                "cma2021",
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                "discrimination",
                "mozilla-cma"
            ],
            "issues": [
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                "Digital Inclusion"
            ],
            "help_types": [],
            "published_by": "Shandukani Mulaudzi",
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            "related_creators": [
                {
                    "name": "Tracey Bowen",
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            ],
            "entry_type": "base",
            "title": "Hope",
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