Bibliographic record
Abstract
The word “memory” comes from “mind” and suggests that what is directly experienced remains in our awareness. Even though no longer physically present, experiences may be called to mind or remembered. The word “voice” or “vocal” comes from “vox” or “vocare,” meaning to call, with its cognates “evoke,” to call forth, and “recall,” to call back. The notion of memory, therefore, may be linked to the voice both calling back and, in a sense, calling forward various experiences of one’s life. To remember is to call back a voice from one’s past, to hear it again in its same form or to give it new voice. Through music, perhaps especially vocal music, we are drawn to return or called back to a place, a time, a person, and with the thoughts, feelings, and associations of that experience that remain with us still. This paper is an attempt to explore the connection of vocal music with memory. Essential elements of this exploration include: the roots or etymologies of words connected with memory and voice; the various dimensions and meanings of memory at the level of thought, feeling, presence, and identity; the inseparably relational dimension of memory; and its flowing not only from the past into the present but also reaching into the future; and the connection of all of these with vocal music. Music may be a link to our human quest to find and express our authentic voice, within a greater relational, communal, and social context.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.007 | 0.015 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".