Appendix E. References and self-audit disclosure¶
The three source volumes¶
| Volume | Title | Version DOI |
|---|---|---|
| Volume I | The 2026 State of Generative Engine Optimization, v1.0 | 10.5281/zenodo.21537014 |
| Volume II | The Absence Ladder. The 2026 State of GEO, v2.0 | 10.5281/zenodo.21586091 |
| Volume III | Divergence Survives a Length Control on Google AI Overviews and Vanishes on Claude. The 2026 State of GEO, v3.0 | 10.5281/zenodo.21789120 |
Measured. All three are published under CC BY 4.0 with their data and analysis code at github.com/Broadcastwell/state-of-geo-2026. Zenodo also issues a concept identifier covering all versions of the series, which resolves to the latest version. It is not a volume and it is cited nowhere in this manual.
Cite Volume III as: Sivakumar, S. (2026). Divergence Survives a Length Control on Google AI Overviews and Vanishes on Claude. Measuring Vendor-Set Agreement Across Four AI Search Engines. The 2026 State of Generative Engine Optimization, v3.0. Zenodo.
External work cited in this manual¶
Reported. The entries below are reproduced from Volume III's reference list, which states that every reference was checked against the arXiv listing or the publisher page before publication, and that author lists are as printed by the source. This manual has not independently re-verified them.
Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., Narasimhan, K., Deshpande, A. (2024). GEO: Generative Engine Optimization. KDD 2024. arXiv:2311.09735.
Bagga, P. S., Farias, V. F., Korkotashvili, T., Peng, T., Wu, Y. (2025). E-GEO: A Testbed for Generative Engine Optimization in E-Commerce. arXiv:2511.20867.
BrightEdge (2026). Why AI Engines Cite Different Sources but Recommend the Same Brands. Weekly AI and Search Insights, 24 April 2026.
Chu, X., Hou, Y. (2026). Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems. arXiv:2606.17443.
DerivateX (2026). ChatGPT and Google AI Overviews agree on tools, not sources. Open benchmark dataset, June 2026.
Harsel, L., Yudina, A., Skopec, C. (2026). AI Overviews are expanding across commercial intent search. Semrush, 2 July 2026.
Jack, W., Lehman, N., Maloney, K., Xu, S. (2026). Prominence-Stratified Failure Modes in Retrieval-Augmented Commercial Recommendation: A 37,000-Run Audit. arXiv:2605.27439.
Jack, W., Lehman, N., Maloney, K., Xu, S. (2026). Divergent Recommendations, Convergent Diagnoses: Cross-Provider Failure-Mode Convergence in AI Commercial Recommendation. arXiv:2606.26116.
Khromova, Y. (2025, updated 2026). ChatGPT vs Perplexity vs Google vs Bing: AI Search Engine Comparison. SE Ranking. Data collected 26 February to 3 March 2025.
Lafferty, N. (2025). AI Platform Citation Patterns. Profound.
McDonald, T., Cooley, H., Williams, M. (2026). AIO Impact on Google CTR: 2026 Update. Seer Interactive, 24 April 2026. Data through February 2026.
Schulte, J., Bleeker, M., Kaufmann, P. (2026). Don't Measure Once: Measuring Visibility in AI Search (GEO). arXiv:2604.07585.
Zatuchin, D. (2026). Who Owns the AI Recommendation? arXiv:2606.23057. Dataset released on Zenodo under CC BY 4.0.
Reported. Volume III notes of Jack and colleagues (arXiv:2606.26116) that the same-prompt rerun baseline quoted in that paper is cited by it from a separate industry report rather than measured within it. This manual repeats that qualification wherever the work is used.
Open flags¶
Reasoned. FLAGS.md at the root of this manual's repository records six open items where a published source is incomplete or two published sources disagree. They are disclosures rather than defects. Where a chapter touches one, it quotes the source as published, asserts no relation between conflicting figures, and does not attempt reconciliation. The current items concern Volume III's answer counts, Volume I's answer and question counts, a duration statement in Volume III, the location of the unique-domain figure, the date on the published self-audit, and the run structure of the August re-measure.
Self-audit disclosure, in full¶
Measured, self-audit of July 2026. In the four-engine, five-run self-audit published alongside Volume II in July 2026, Broadcastwell was named in 0 of 200 answers and cited 0 times among 663 citations. The structure was four engines, ten questions, five runs per question. That published figure stands with its date and is never replaced. The July date is taken from the published citation metadata rather than from the disclosure sentence itself, which gives no month, and that is recorded as an open flag.
Measured, self-audit of 18 August 2026. Re-measured on the same ten published questions across the same four engines, at one run per question rather than five, between 03:51 and 04:03 UTC on 18 August 2026: Broadcastwell was named in 1 of 40 answers and cited once among 674 citations. Forty of forty calls returned a scored answer and no engine failed.
Measured, self-audit of 18 August 2026. The single naming and the single citation are the same answer. One engine, answering a comparison question about two other agencies, quoted Broadcastwell's own published visibility page as a source and named Broadcastwell as the publisher of that page.
Reasoned. That is a citation of the research and not a recommendation of the firm. Reported as a visibility result it would look like an agency appearing in an answer, and it is instead a live instance of the pattern in Chapter 3 at /cited-not-recommended/. Anybody quoting the 1 of 40 as evidence of visibility, including this firm, would be quoting a number whose content contradicts its headline.
Reasoned. The two lines are not directly comparable, because one rests on five runs per question and the other on one. Neither replaces the other and both are published on every page of this manual with their dates and run structures attached. The reason for publishing both is that a manual asking buyers to demand evidence should be measurable on the same terms it sets.
Licence and status¶
Measured. Prose and figures in this manual are published under CC BY 4.0. The site code is MIT. Nothing here has been through academic peer review: it is measurement published with the data and code that produced it. The standing invitation is to recompute any figure you doubt from the public files and publish what you get, including a result that contradicts one of these.
Attribution¶
Sivakumar, S. (2026). The Absence Manual. Broadcastwell. docs.broadcastwell.com
Sources¶
The volume identifiers and citation formats are from the published Zenodo records and the source repository. The external reference list is reproduced from Volume III. The self-audit figures are the operator's own, published with their dates and run structures. Everything is at github.com/Broadcastwell/state-of-geo-2026.
About this manual¶
Author. Sairam Sivakumar, Broadcastwell.
Operator disclosure. Broadcastwell ran this measurement and sells services in the category it measures. Broadcastwell is excluded from the measured sample and from every ranking. The mitigation is not that the conflict is absent, it is that the raw data and the code are public and the result can be recomputed by anyone who disagrees.
Self-audit, July 2026. In the four-engine, five-run self-audit published alongside Volume II in July 2026, Broadcastwell was named in 0 of 200 answers and cited 0 times among 663 citations. That published figure stands with its date and is never replaced.
Self-audit, 18 August 2026. Re-measured on the same ten published questions across the same four engines, at one run per question rather than five, between 03:51 and 04:03 UTC on 18 August 2026: named in 1 of 40 answers, and cited once among 674 citations. The single naming and the single citation are the same answer, in which the engine quoted Broadcastwell's own published visibility page as a source. The two lines are not directly comparable, because one rests on five runs per question and the other on one.
Not peer reviewed. This is an independent industry study published as an open dataset with the analysis code that produced every figure in it. It has not been through academic peer review. Read it as measurement, and check the measurement. If you disagree with a number here, recompute it from the public data and publish what you get.
Licence. Prose and figures CC BY 4.0. Site code MIT.
The three volumes.
| Volume | What it covers | DOI |
|---|---|---|
| Volume I | 85 companies, 61 categories, 860 scored answers and 5,160 citations, one engine held constant. The dataset README additionally records 1,753 unique domains cited | 10.5281/zenodo.21537014 |
| Volume II | The Absence Ladder. All 616 absence records classified by question shape | 10.5281/zenodo.21586091 |
| Volume III | Cross-engine divergence. 280 questions, 40 categories, four engines, 853 answers | 10.5281/zenodo.21789120 |
Data and analysis code for all three volumes: github.com/Broadcastwell/state-of-geo-2026.
Version 1.0, August 2026.