🌻 Lonely in London response#

24 Jan 2026

Author Response to Reviewers#

Reviewer key: G = Gemini, C = Claude, O = OpenAI (GPT)


Several reviewers ask me to correct the inner paper’s overstatement of rigor (journal completeness, quote misattributions). O G C

I already disclosed these in my reflection: the journal was not maintained as claimed; and I found two quote errors (“limitations for young people” in Interview 26—not verbatim; “being out and about” in Interview 35, not 13). I will not revise the inner paper to fix them. The experiment presents the AI’s output as written; the reflection documents its errors. Correcting the inner paper would contradict the purpose of the exercise.

Thin excerpts / limited literature (O C)
The inner paper has sparse verbatim evidence but it is a short paper. I already acknowlege that there is little substantive literature engagement. I will not rewrite the inner paper. I will acknowledge in my wrapper that excerpt density and literature context are limitations.


n=16 per borough vs 48 total (O)
The inner paper states “n=16 per borough” across four boroughs (16×4=64) but the total is 48. I did not catch this arithmetic error. I will add a note in my wrapper section listing it among the AI’s uncorrected errors.


These are more formal and don't really matter at this point, as the paper was accepted

Anonymity (O C)
GitHub link and identifying self-citations (Powell & Caldas Cabral; causal mapping) will be removed or anonymised for review.

AI Involvement Checklist (O)
Writing score 3.5 is invalid (scale 1–4). I will correct to a valid score.

Formatting (O C)
References, headings, and template alignment will be brought into line with the CFP.

Authorship and voice (O C)
The inner paper uses “we” despite there being no human co-author. I will add an explicit note in my wrapper: who is speaking in the inner paper; what the human did (dataset choice, instruction framing, post-hoc checking, revision prompts); and where interpretive authority lies.

Autoethnographic reflection too thin (O C G)
I will expand the reflection to address the emotional/experiential dimension: what it felt like to watch the AI interpret vulnerable people’s accounts; moments of wanting to intervene; how “no actual person is the author” sat with me.

Model transparency (O C G)
I will specify the underlying model (Cursor’s default at the time) for reproducibility.

Ethics of AI processing (O C)
The data is already anonymised and public, but I will add a paragraph on data handling.


Negative-case search claimed as “systematic” (O G C)
The inner paper says “deliberate negative-case search” (3.4) and “we deliberately searched for transcripts” (3.3). It never claims a “systematic pass.” My reflection incorrectly stated that the paper claims a systematic negative-case pass; the reviewers echoed that. I will correct my reflection.