Monopoly, monopsony, and the value of culture in a digital age: An axiology of two multimedia resource repositories
Bibliographic record
Abstract
Broadly speaking, axiology is the study of values. Axiologies are expressed materially in patterns of choices that are both culture-bound and definitive of different cultures. They are expressed in the language we use; in the friends we keep; in the clothes we wear; in what we read, write, and watch; in the technologies we use; in the gods we believe in and pray to; in the music we make and listen to—indeed, in every kind of activity that can be counted as a definitive element of culture. In what follows, I describe the axiological underpinnings of two closely related multimedia repository projects— Australian Creative Resources Online (ACRO) and The Canadian Centre for Cultural Innovation (CCCI)—and how these are oriented towards a potentially liberating role for digital repositories.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.009 | 0.035 |
| Scholarly communication | 0.023 | 0.019 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".