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=-entry_type&page=36
HTTP 200 OK
Allow: GET, POST, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "count": 1758,
    "next": "https://api.mozillapulse.org/api/pulse/v2/entries/?ordering=-entry_type&page=37",
    "previous": "https://api.mozillapulse.org/api/pulse/v2/entries/?ordering=-entry_type&page=35",
    "results": [
        {
            "id": 2526,
            "content_url": "https://foundation.mozilla.org/en/blog/truth-challenges-changes-algorithmic-bias-against-black-women/",
            "is_bookmarked": false,
            "tags": [
                "mozilla-cma"
            ],
            "issues": [
                "Digital Inclusion"
            ],
            "help_types": [],
            "published_by": "Kevin Zawacki",
            "submitter_profile_id": 82,
            "bookmark_count": 0,
            "related_creators": [],
            "entry_type": "base",
            "title": "TRUTH",
            "description": "TRUTH — an interactive web experience and physical art installation — highlights stories by Black women, about Black women. The stories touch on family, strength, creativity, and ambition, and provide a sorely-needed alternative to the existing “data” that is online.",
            "get_involved": "",
            "get_involved_url": "",
            "interest": "",
            "featured": false,
            "published_by_creator": false,
            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2023-04-05_175014.1819050000.png",
            "created": "2023-04-05T17:50:14.181685Z",
            "moderation_state": 3
        },
        {
            "id": 2527,
            "content_url": "https://rewardreports.github.io/",
            "is_bookmarked": false,
            "tags": [
                "audit tools",
                "mozilla-mtf",
                "mozilla technology fund"
            ],
            "issues": [
                "Openness"
            ],
            "help_types": [
                "Test & feedback"
            ],
            "published_by": "Shandukani Mulaudzi",
            "submitter_profile_id": 5750,
            "bookmark_count": 0,
            "related_creators": [
                {
                    "name": "Graduates for Engaged and Extended Scholarship in Computer Science and Engineering (GEESE)",
                    "profile_id": 6330,
                    "is_active": false
                }
            ],
            "entry_type": "base",
            "title": "Reward Reports",
            "description": "Current AI documentation tools are able to account for model outputs, but not for outcomes generated by the system itself over time. For the past year, the team at the Graduates for Engaged and Extended Scholarship in Computer Science and Engineering (GEESE) have developed Reward Reports to address this gap. Reward Reports is an audit tool for comparing a system’s observed behaviors with the assumptions and expectations of its designers.",
            "get_involved": "",
            "get_involved_url": "",
            "interest": "",
            "featured": false,
            "published_by_creator": false,
            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2023-05-10_100228.2005790000.png",
            "created": "2023-05-10T10:02:28.200255Z",
            "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",
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            "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.",
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            "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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            "bookmark_count": 0,
            "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": "",
            "get_involved_url": "",
            "interest": "",
            "featured": false,
            "published_by_creator": false,
            "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": [
                "Openness"
            ],
            "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": "",
            "get_involved_url": "",
            "interest": "",
            "featured": false,
            "published_by_creator": false,
            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2023-05-10_101808.3105630000.png",
            "created": "2023-05-10T10:18:08.310319Z",
            "moderation_state": 3
        },
        {
            "id": 2531,
            "content_url": "https://docs.tracking.exposed/guardoni/guardoni-intro/",
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            "tags": [
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                "mozilla-mtf",
                "mozilla technology fund"
            ],
            "issues": [
                "Openness"
            ],
            "help_types": [],
            "published_by": "Shandukani Mulaudzi",
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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,
            "published_by_creator": false,
            "thumbnail": "https://assets.mofoprod.net/network-pulse/images/entries/2023-05-10_103039.5722810000.jpg",
            "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-mtf",
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            "issues": [
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            ],
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            "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.",
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            "featured": false,
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            "created": "2023-05-10T10:32:41.807623Z",
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            "id": 2534,
            "content_url": "https://wonyoung.so/",
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            "tags": [
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            ],
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            "help_types": [],
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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.",
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            "featured": false,
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            "created": "2023-05-10T10:36:19.041970Z",
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        {
            "id": 2535,
            "content_url": "https://www.datakind.org/",
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                "data",
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            "issues": [
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            "published_by": "Shandukani Mulaudzi",
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            "entry_type": "base",
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            "description": "DataKind is a global nonprofit headquartered in the U.S. that seeks to leverage data science for the greater good. Working in collaboration with the Black Wealth Data Center, DataKind will create an interactive data tool to help community leaders, policymakers, and access providers understand broadband inequalities in the U.S. Leveraging existing but dispersed data and a network of collaborators, DataKind aspires to shine a light on where “digital deserts” exist, and how different communities are impacted by them.",
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        {
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            "content_url": "https://ooni.org/",
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            "issues": [
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            "entry_type": "base",
            "title": "POSMO",
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            "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.",
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            "entry_type": "base",
            "title": "Tidepool",
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            "content_url": "https://foundation.mozilla.org/en/blog/announcing-kenyas-inaugural-cohort-of-responsible-computing-challenge-awardees/",
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            "title": "Mozilla’s Responsible Computing Challenge Opens Applications In India",
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            "created": "2023-11-15T16:11:39.922523Z",
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        },
        {
            "id": 2543,
            "content_url": "https://www.herinternet.org/about-us/",
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            "tags": [
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            "issues": [
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            "help_types": [],
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            "entry_type": "base",
            "title": "The impact of Algorithms on LGBTQ organising in Uganda",
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            "content_url": "https://foundation.mozilla.org/en/blog/mozilla-announces-seven-africa-mradi-research-grantees/",
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            "tags": [
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