Henry Cleere: The Lone Ranger of World Heritage Evaluations (1992-2002)
Bibliographic record
Abstract
This article focuses on the decade from 1992 to 2002 when Henry Cleere served as the ICOMOS coordinator for World Heritage nominations. Based on his interview with the author as part of her World Heritage Oral Archives project as well as her personal recollections, the article recounts his initiation into the politics of World Heritage at his first session when he encountered a fait accompli for the nomination of Angkor (Cambodia). It highlights the triumphs and frustrations of his work over the decade, as recounted in no uncertain terms by Henry himself. The single-evaluator model that he inherited from his predecessor challenged his capacity to manage an ever-increasing workload and took its toll on his health. Subsequently the model was expanded by ICOMOS to include a team of evaluators. Henry’s years as ICOMOS coordinator were remarkably productive. He carried out research and prepared advice for the Committee on about 350 nomination proposals. Through his experience and professional knowledge, he also proposed improvements to the evaluation process for World Heritage cultural properties, in particular by introducing ICOMOS missions to the sites and by insisting on conservation and management issues. The article contains contextual information drawn from UNESCO documents as well as lively quotations from Henry and several of his contemporaries drawn from the World Heritage Oral Archives. They confirm the significant contribution that Henry made to World Heritage and his heroic efforts to sustain the lone-ranger model in the face of a rapidly expanding system.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".