Bibliographic record
Abstract
Over the past twenty years, what constitutes a culture’s heritage has been debated amongst those responsible for governmental policies, as well as the constituents that governments serve. While heritage has often focused on tangible items – architecture and the material world – recent policies have broadened the focus to include the intangible: knowledge, ideas, performances, beliefs handed down for generations. Many national and international agencies – lead by UNESCO – now have policies and programs that deal with intangible cultural heritage (ICH). Within the Canadian context, the federal government has had differing interpretations of the importance of this type of heritage. Most recently, in spite of initial involvement in its drafting, the Department of Canadian Heritage has decided not to support UNESCO’s new international ICH Convention, which went into force in April, 2006, and now includes more than 160 countries that have ratified it. Historically, provincial governments and NGOs across Canada have been more involved with ICH, and it is here that the most recent initiatives are occurring. The changing stance of the Department of Canadian Heritage on this topic may well be related to specific figures involved, unspoken fears of legal repercussions, and the lobbying of special interest heritage groups.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.021 | 0.012 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 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".