Defining the Modern Museum: A Case Study of the Challenges of Exchange
Bibliographic record
Abstract
The entry point of Defining the Modern Museum is the claim that the modern museum, a synecdoche of the intellectual and physical World (singular and capitalized), has been a powerful yet mythical idea, impossible to be materially accomplished. Rather than focusing on theoretical – therefore ideal – paradigms of what a museum should be, Lianne McTavish’s goal is to apply critical theory to the (historically traceable) practices of one institution in particular: the New Brunswick Museum (NBM), the oldest continuing museum in Canada. Throughout the volume, the writer criticizes the abundance of investigations that use her same theoretical scope, yet to ultimately prove the democratic success of certain contemporary museum models, or the commodification and dissolution of this type of institution into mere massive spectacle. She warns readers that her endeavor in Defining the Modern Museum is to identify continuities and contradictions rather than offer a definite diagnosis of this institution or museums at large.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.029 | 0.022 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".