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Record W115209551 · doi:10.7275/6054877.0

A Preliminary Model of Dignity Management in Hospice

2021· article· en· W115209551 on OpenAlexaboutno aff
Qiaohong Guo

Bibliographic record

VenueScholarworks (University of Massachusetts Amherst) · 2021
Typearticle
Languageen
FieldMedicine
TopicPatient Dignity and Privacy
Canadian institutionsnot available
Fundersnot available
KeywordsDignityBusinessPolitical scienceLaw

Abstract

fetched live from OpenAlex

The traditional vocal music of Nova Scotia is a collage of genres reflecting its population and distinct history. Serving as a historic nautical gateway between North America and Europe, the continuous influx of populations led to the formation of many communities ranging from the urban epicenter of Halifax to the smallest of rural communities and coastal outports. Though largely akin to the musical traditions of the Western European colonizers of the 17th-19th centuries (predominantly English, Irish, Scottish, German, and French), the combination of song variants, repertoires from other cultures and traditions, and original compositions led to the emergence of a uniquely Nova Scotian canon. Acknowledging that previous scholarship, economic, and editorial forces had a direct influence concerning what musics were explored, gathered, and promoted, this dissertation examines the published transcriptions of Nova Scotian traditional vocal repertoires spanning 1912-2005. I restrict this study to the repertoire encoded in conventional pitch labels of the Western European tradition, as that was the medium through which previous transcribers of these oral repertoires encoded this music. This repertoire is examined through quantitative inquiry, employing set-class theory and successive interval arrays. Through the creation of tonic-based successive-interval arrays for nearly two thousand melodies spanning twenty-seven publications, I present a meta-analysis of the pitch-spaces encoded by the transcribers of this repertoire and identify normative collection sizes, scalar patterns, and outliers. I also make new transcriptions, based on commercially available field recordings of attributed source materials, to enable a cursory comparison and audit of previous transcriptions in order to comment on the quality and issues surrounding differing interpretations. The pedagogical merits of using the tonic-based successive-interval array for teaching music spanning a limited number of pitches, containing chromaticism, and modal repertoire is also explored. As such, this work serves to assemble and present a detailed overview of transcribed materials in print.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.704

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.246
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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Same venueScholarworks (University of Massachusetts Amherst)Same topicPatient Dignity and PrivacyFrench-language works237,207