The Greening of Hymnody, Part 4: Remembering to Not-Forget: Congregational Singing with All of Creation
Bibliographic record
Abstract
Daphne the dog has a very good memory. That mink she once spied slipping into culvert is forever etched into her retina in such a way every culvert must be investigated just in case a mink might be lurking there. Long unseen stuffed -animal dog-toy friends, like lost pennies once found, are instantly restored to her collection of treasures. And of course an impending thunderstorm, with its aggressive high winds, foreshadows the tent (or house or car or wherever Daphne happens to be resting her paws at the time) will inevitably collapse over her head yet again. Daphne is good at not- forgetting. Members of the Body of Christ are expected to not-forget and strive to be good at not-forgetting. Christ exhorts his follower friends to anamnesis - to recollection, bearing in mind, remembrance - of his leading their ritual meal, to keep it alive, and not let it slip into a forgotten past: to not forget. In the greening of hymnody, might we best not-forget knowledge humanity has held for aeons? Michael Hawn has given us a very helpful image of streams of traditions in congregational song. He shows how these streams have intermingled in the past, and how they can and do intermingle today. Canadian poet Rae Crossman speaks of a concept of life-giving confluence among people living and working and playing together in a community of creativity: rivers flow into rivers reflection scatters into spindrift wind wails into psalm so music flows into the bloodstream dance into the bones words breathe a brush stroke quivers a pulse . . . rivers flow into rivers I am a tributary of you you are a branch of me our waters swirl into clouds we we In the greening of our hymnody we have an opportunity to river and rain with our congregational song: to give oral and aural lives to our texts feed and grow our imaginations. But are we sometimes guilty of not remembering the sources of the sounds we use in our interpretations and the leading of our congregational singing? While the voice is the most local and individual primary voice - our Mennonite friends have certainly not forgotten this - the musical leading of our congregational singing is often done through instruments. But, as R. Murray Schafer challenges, that the material of a musical instrument may have a home other than its carrying case, or it might inwardly be longing to return to its native element, is a notion never occurs to a Western musician today. Or if it did, it would be embarrassing, since many of the materials, like the wood of the Brazilian forest, are the products of plundering: gold, silver, ebony, ivory, the rosewood of xylophones, the grandula of oboes. These aren't materials from your back yard; they come mostly from Africa, Asia and South America, and were originally taken by colonial powers to Europe, where they were fashioned into instruments, trophies, you might say. A First Nations Elder recently led me through the process of making a hand drum out of the beginnings of the skin of a deer and the wood of a cedar tree. …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".