ICO Case Allocation Letter Regarding FOIA Complaint Against King's College London (Redacted Version, 29 October 2025)
Bibliographic record
Abstract
This document contains the fully redacted case allocation notice issued by the UK Information Commissioner’s Office (ICO) on 29 October 2025, concerning the FOIA complaint filed in connection with King’s College London’s handling of information requests regarding Walter Homolka’s 1992 PhD thesis and related allegations of academic misconduct. The letter confirms allocation of the case to a Senior Case Officer, outlines the expected timeline for KCL’s submission, and states that further progress will be made once additional information is received from the university. All personal data not belonging to the requester has been redacted in accordance with UK GDPR requirements. This redacted release is provided for the purpose of transparency, documentation of FOIA processes, and academic accountability. --- **Suggested citation:** Fehige, Y. (2025). *ICO Case Allocation Letter Regarding FOIA Complaint Against King’s College London (Redacted Version, 29 October 2025)* (1.0 — Redacted Release). Zenodo. https://doi.org/10.5281/zenodo.17715812
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.021 | 0.007 |
| Insufficient payload (model declined to judge) | 0.465 | 0.396 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".