The Heritage Village: Sifting through Immaterial Histories of Land
Bibliographic record
Abstract
This paper considers the immaterial aspects of the history of land as way to reimagine heritage. Through the heritage village – that imagined, artificial, and curated representation of history with very particular kinds of material iterations and legacies of the past – we consider the immaterial memories and histories that have becomes absent from the staging and design of heritage as collective history. We consider the way that these omissions function in the imagination of the present and future by turning to the site-specific contemporary art exhibition Land/Slide Possible Futures (2013). Located on the site of Markham Museum heritage village in Ontario, Canada, this expansive project reveals the imbricated histories of the rise of the heritage village and that of the suburb. Turning in particular to Duke & Battesby’s Always Popular, Never Cool and Terrance Houle’s There’s Things That Even a Drunk Will Never Forget, we argue for the heritage village as a lieu de mémoire, where memories are continuously unearthed, revealed, and imagined, and where artists transform archival collections and historical architectures into surreal and uncanny encounters with those pasts that are immaterial and absent from the facades of 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.028 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".