--- title: "readforgood.org in the Machine Relations Index" description: "readforgood.org appeared as a cited source in 2 of 39,509 monitored answer runs (under 0.01%) from 2026-05-10 to 2026-11-14." canonical: "https://machinerelations.ai/index/domains/readforgood.org" --- # readforgood.org in the Machine Relations Index readforgood.org appeared as a cited source in 2 of 39,509 monitored answer runs (under 0.01%) from 2026-05-10 to 2026-11-14. Canonical URL: https://machinerelations.ai/index/domains/readforgood.org Canonical domain: readforgood.org Source role: Other observed source Release mri_score_v2.1+2026-11-14+a5e5e37df8da; methodology mri_score_v2.1; generated 2026-11-14; window 2026-05-10 to 2026-11-14; artifact 90bc78b19db1. ## Overall Evidence - Citation rate: under 0.01% - Cited runs: 2 of 39,509 - Days cited: 2 of 182 - Engine breadth: 1 observed engine (perplexity) - Confidence: Collecting - Standing: Collecting: no rank until it clears the evidence floor ## Observed Segments | Category | Question shape | State | Cited runs | Observed runs | Run dates | Rate | Standing | |---|---|---|---:|---:|---:|---:|---| | [Professional Services](https://machinerelations.ai/index/categories/professional-services) | [Problem-first research](https://machinerelations.ai/index/categories/professional-services/problem_first) | published | 2 | 139 | 8 | 1.44% | #83 of 227 | ## Citation History readforgood.org was first cited in a monitored answer run on October 28, 2026, and most recently on November 14, 2026, with cited runs in each of the 2 months from then to this release. The release window opens 2026-05-10, so an earlier citation would not show here. A month's rate is the share of all monitored answer runs that month that cited this domain. The latest month is still collecting. | Month | Cited runs | Observed runs | Rate | |---|---:|---:|---:| | October 2026 | 1 | 16,496 | 0.01% | | November 2026 (to 2026-11-14) | 1 | 5,026 | 0.02% | ## By Answer Engine An engine's rate is its cited runs over every monitored run that engine answered in the window. Engines answer different numbers of runs, so compare rates, not counts. | Engine | Cited runs | Engine's observed runs | Rate | |---|---:|---:|---:| | [Perplexity](https://machinerelations.ai/index/engines/perplexity) | 2 | 9,530 | 0.02% | | [ChatGPT](https://machinerelations.ai/index/engines/chatgpt) | 0 | 9,410 | 0.00% | | [Claude](https://machinerelations.ai/index/engines/claude) | 0 | 9,359 | 0.00% | | [Gemini](https://machinerelations.ai/index/engines/gemini) | 0 | 7,598 | 0.00% | | [Google AI Mode](https://machinerelations.ai/index/engines/google_ai_mode) | 0 | 2,237 | 0.00% | | [Google AI Overviews](https://machinerelations.ai/index/engines/google_ai_overviews) | 0 | 1,375 | 0.00% | Since August 31, 2026, readforgood.org is cited in none of 1,031 observed Google AI Mode runs. Google AI Mode's collection changed between August 10, 2026 and August 30, 2026, so its row above pools both sides of the change. Since October 7, 2026, readforgood.org is cited in 2 of 4,761 observed Perplexity runs (0.04%). Perplexity's collection changed between October 6, 2026 and October 7, 2026, so its row above pools both sides of the change. ## Peers readforgood.org holds its best segment rank, #83 of 227, in Professional Services / Problem-first research, at 1.44%. 43 sources on that leaderboard share that rate, and their order inside the tie is not a measured difference. Listed here: the nearest sources cited more and less often than it, and the sources beside it that share this best segment. Leaderboard: https://machinerelations.ai/index/categories/professional-services/problem_first | Rank | Source | Source role | Segment citation rate | Against this source | |---|---|---|---:|---| | #41 of 227 | [smartbrief.com](https://machinerelations.ai/index/domains/smartbrief.com) | Editorial publication | 2.16% | +0.72 pts | | #42 of 227 | [strategiclearning.asia](https://machinerelations.ai/index/domains/strategiclearning.asia) | Other observed source | 2.16% | +0.72 pts | | #43 of 227 | [thepoiriergroup.com](https://machinerelations.ai/index/domains/thepoiriergroup.com) | Analyst and consulting research | 2.16% | +0.72 pts | | #82 of 227 | [punchfinancial.com](https://machinerelations.ai/index/domains/punchfinancial.com) | Other observed source | 1.44% | Same rate | | #84 of 227 | [sprintlaw.co.uk](https://machinerelations.ai/index/domains/sprintlaw.co.uk) | Other observed source | 1.44% | Same rate | | #205 of 227 | [talkerstein.com](https://machinerelations.ai/index/domains/talkerstein.com) | Other observed source | 0.72% | -0.72 pts | | #206 of 227 | [taxstra.com](https://machinerelations.ai/index/domains/taxstra.com) | Other observed source | 0.72% | -0.72 pts | | #207 of 227 | [thebookkeepingxperts.com](https://machinerelations.ai/index/domains/thebookkeepingxperts.com) | Other observed source | 0.72% | -0.72 pts | ## Citation Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai. readforgood.org, under 0.01% citation rate, 2 of 39,509 monitored answer runs, 2026-05-10 to 2026-11-14. Release mri_score_v2.1+2026-11-14+a5e5e37df8da. CC BY 4.0. https://machinerelations.ai/index/domains/readforgood.org APA Parrott, J. (2026). readforgood.org in the Machine Relations Index (Version mri_score_v2.1+2026-11-14+a5e5e37df8da) [Data set]. Machine Relations Research. https://machinerelations.ai/index/domains/readforgood.org https://doi.org/10.5281/zenodo.23652423 BibTeX ```bibtex @misc{parrott2026mrireadforgoodorg, author = {Parrott, Jaxon}, title = {readforgood.org in the Machine Relations Index}, year = {2026}, version = {mri\_score\_v2.1+2026-11-14+a5e5e37df8da}, publisher = {Machine Relations Research}, url = {https://machinerelations.ai/index/domains/readforgood.org}, doi = {10.5281/zenodo.23652423}, license = {CC-BY-4.0}, note = {Machine Relations Index (MRI), Machine Relations Research — machinerelations.ai} } ``` DOI: https://doi.org/10.5281/zenodo.23652423 Citation file: https://machinerelations.ai/CITATION.cff ## Badge Badge image: https://machinerelations.ai/index/domains/readforgood.org/badge.svg [![readforgood.org in the Machine Relations Index: cited in under 0.01% of monitored AI answers (2 of 39,509 runs), Nov 14, 2026 release. Machine Relations Research.](https://machinerelations.ai/index/domains/readforgood.org/badge.svg)](https://machinerelations.ai/index/domains/readforgood.org) Put this badge on your site to show how often AI answers cite it. It links to this profile and updates with every new release; if a later release no longer includes this domain, the badge stops loading. To keep today's numbers fixed, save the SVG and host it yourself. ## Use the data The public JSON is https://machinerelations.ai/data/machine-relations-index.json. The release manifest is https://machinerelations.ai/data/mri-release-manifest.json. The domain CSV is https://huggingface.co/datasets/machine-relations/machine-relations-index/resolve/main/domains.csv. The Zenodo concept DOI is https://doi.org/10.5281/zenodo.23652423. ```bash curl -fsSL "https://machinerelations.ai/data/machine-relations-index.json" -o machine-relations-index.json curl -fsSL "https://machinerelations.ai/data/mri-release-manifest.json" -o mri-release-manifest.json curl -fsSL "https://huggingface.co/datasets/machine-relations/machine-relations-index/resolve/main/domains.csv" -o domains.csv curl -fsSL -L "https://doi.org/10.5281/zenodo.23652423" -o mri-zenodo.html ``` ```python import json from urllib.request import urlopen index_url = "https://machinerelations.ai/data/machine-relations-index.json" with urlopen(index_url) as response: index = json.load(response) print(index["generated"], index["total_domains"]) ``` ## Public Boundary The public dataset reports citation rates, rankings, and evidence counts. It excludes internal query identifiers, raw cited URLs, and answer-engine provider payloads. MRI measures observed root-domain citations in monitored prompts; it does not measure all AI answers, recommendation quality, website traffic, or commercial performance. A citation does not prove source support, and MRI confidence is not an Answer-Source Fidelity grade. ## Related Sources - [Machine Relations Index](https://machinerelations.ai/index) - [Public JSON artifact](https://machinerelations.ai/data/machine-relations-index.json) - [Release manifest](https://machinerelations.ai/data/mri-release-manifest.json)