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Record W4296143885 · doi:10.1111/nin.12528

Social acceleration, alienation, and resonance: Hartmut Rosa's writings applied to nursing

2022· article· en· W4296143885 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNursing Inquiry · 2022
Typearticle
Languageen
FieldMedicine
TopicPatient Dignity and Privacy
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAlienationEthosSociologyHealth careModernityEpistemologyNursingPsychologyMedicinePhilosophyPolitical science

Abstract

fetched live from OpenAlex

This article aims to present the life and work of German thinker Hartmut Rosa as a philosopher of interest for nursing. Although his theoretical framework remains fairly unknown in the nursing domain, its main key concepts open up a philosophical and sociological approach that can contribute to the understanding of a wide range of study phenomena related to nurses, nursing, and healthcare. The concepts of social acceleration, alienation, and resonance are useful to explore healthcare organizations' performance by bringing the time dimension of modernity to the center; to grasp nurses' experiences of caring for patients; and to understand nurses as agents endowed with the capacity to deploy their political agency to create alternative forms of relationship to themselves, to others, and the world, challenging the institutional order of healthcare organizations when it fails to resonate with their professional ethos. In this article, we propose Hartmut Rosa's theoretical framework as a new and inspiring phenomenological and critical lens that should be further explored to advance knowledge concerning phenomena that are found at the crossroads of the nursing domain and other fields of knowledge.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.505
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.089
GPT teacher head0.366
Teacher spread0.277 · 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