Bibliographic record
Abstract
Industrial heritage artifacts may include the industrial products, technologies and infrastructures that have contributed to modernization beginning with the Industrial Revolution. The history of our industrial heritage spans 50 to 150 years and can be characterized by taking into account the site and the technology. This paper analyzes 13 precedents in Japan, Canada, and the United States in terms of these concerns, with focus on the reuse of abandoned mines as industrial heritage. Field surveys and interviews about each abandoned mine were used to obtain historical records and material. The results describe progress in three phases (1) recognizing phase, (2) organizing phase, and (3) maintenance management phase. A proper methodology for reuse is necessary to ensure the authenticity of the abandoned mine, particularly in the face of poor tourism-oriented approaches. As a result of analyzing the 13 cases, we determined that the following principles should be considered during the reuse process. Firstly, reuse of abandoned mines should not be compulsory but should be a spontaneous process and especially, should be carried out by inhabitants. Secondly, education and real experiences in the abandoned mine should be used to ive visitors a feeling of authenticity. Thirdly, creative remodeling methods can be used to enhance the abandoned mine's facilities and the site. Finally, historic and new functions should be the focus of the revitalization. Because this paper mainly focused on 13 precedents, there are likely more diverse cases. However, the conclusions of this report have practical value for reuse of abandoned mines and can be used in establishing methods for reusing Korean abandoned mines as industrial heritage.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".