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Record W2773399280 · doi:10.1177/1077800417745101

Eight Events for Entering a PhD: A Poetic Inquiry Into Happiness, Humility, and Self-Care

2017· article· en· W2773399280 on OpenAlexafffund
Amber Moore

Bibliographic record

VenueQualitative Inquiry · 2017
Typearticle
Languageen
FieldMedicine
TopicEmpathy and Medical Education
Canadian institutionsUniversity of British Columbia
FundersUniversity of British Columbia
KeywordsPoetryHumilityHappinessScholarshipEvent (particle physics)SociologyAestheticsPsychologyLiteratureSocial psychologyPhilosophyArtLawTheology

Abstract

fetched live from OpenAlex

These two poetry clusters comprised a total of eight poems that offer (a) reflective, “past” event poetry and (b) hopeful “humbling” event pieces for future use. Inspired by scholarship examining novice academics’ emotions upon entering graduate school, each poem outlines a potential path to accessing happiness, humility—an especially important quality in graduate school, particularly while writing—and ideas for self-care. As such, through poetic inquiry, which encourages “poetic living,” this article offers avenues for engaging with authorial voice through “vox autobiographia/autoethnographia,” to confront emotional “messiness,” with a “tender” poetic approach.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.991
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.012
Scholarly communication0.0060.005
Open science0.0010.006
Research integrity0.0010.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.149
GPT teacher head0.475
Teacher spread0.325 · 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 source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
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

Citations5
Published2017
Admission routes2
Has abstractyes

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