A Critical Exploration of Frameworks for Assessing the Significance of New Zealand’s Historic Heritage
Bibliographic record
Abstract
This study argues that considerations of value and significance are fundamental to sustainable heritage management practice. It explores critical issues relating to the valorisation of historic heritage in New Zealand and considers whether existing frameworks for evaluation and assessment are effective and appropriate. The two frames of reference comprise: firstly, theoretical principles relating to the nature and qualities of heritage value and secondly, operational strategies relating to the process ofassessment. The study integrates current policy and practice within existing epistemology with primary research data using a mixed methodology. A review of international policy and practice contrasts the various approaches used in Australia,Canada, England and the United States of America, and identifies effective system characteristics. Existing understandings and practice within New Zealand are considered and analogies made between particular elements of the primary research drawn from surveys of professional and non-professional opinion of the heritage assessment process. The New Zealand findings are then set against the review of international evidence and the literature to identify significant strengths and shortcomings.
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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 | 0.034 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.008 | 0.049 |
| Scholarly communication | 0.021 | 0.013 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".