Bibliographic record
Abstract
Advocacy can be a useful tool. But like all tools it has its limitations and potential dangers, its proper and improper uses. Understanding the difference is critical. Advocacy and philosophy are very different processes, serving very divergent ends. Philosophy is suited poorly to advocacy’s political purposes, and advocacy arguments are seldom of much philosophical worth. Advocacy is conservative, a plea for support of the status quo. Philosophy has no such encumbrances, no preordained agenda. Viewed philosophically, musical engagements are not unconditionally good: they may harm as well as heal, subvert as well as advance the goals of education. The need for advocacy often stems from educational failings. Because there is no inherent linkage between musical involvements and educational outcomes, and because the validity of advocacy arguments always rests upon particular instructional practices, advocacy arguments should be undertaken judiciously, and locally by the professionals charged with delivering the goods.
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 | 0.028 | 0.110 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.022 |
| Scholarly communication | 0.018 | 0.025 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.019 | 0.015 |
| Insufficient payload (model declined to judge) | 0.025 | 0.008 |
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".