Publishing Privileges the Published: An Analysis of Gender, Class, and Race in the Hymnological Feedback Loop
Bibliographic record
Abstract
Hymnal curation processes have for centuries maintained restrictive feedback loops: material that has been published elsewhere continues to be published, and new material—particularly when it offers something unique—is evaluated against the criteria of what has gone before. This results in hymnals that tend to over-represent the work of white male contributors from a Euro–American perspective and limits the amount of material by women, people of color, and contributors from around the world. Since the mid-to-late twentieth century, when some denominations have sought to diversify their worship music collections, change has come slowly. Contemporary hymnody and contemporary worship music are predominantly written by men, and additions of global song have relied on a narrow swath of scholars and publications. To understand some of the power imbalances embedded in church music publishing, we use Voices Together, the 2020 Mennonite hymnal for which we were committee members, as a case study. We explore how this new collection came to include only about 45 newly published songs out of the total of 749 songs, and we analyze statistics related to gender and global song. An intersectional approach allows us to examine how musical actors are marginalized in multiple ways, considering prejudice against class, race, and gender. Understanding how current collections are informed by previously published collections, and consequently how the demographics of contributors have shifted over time, explains how publishing privileges the published and offers insight needed to begin to rectify this problem.
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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 | 0.010 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".