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Record W2792209042 · doi:10.18432/ari29368

Creating a Warmth Against the Chill: Poetry for the Doctoral Body

2018· article· en· W2792209042 on OpenAlexvenueno aff
Esther Fitzpatrick, Mohamed Alansari

Bibliographic record

VenueArt/Research International A Transdisciplinary Journal · 2018
Typearticle
Languageen
FieldHealth Professions
TopicDoctoral Education Challenges and Solutions
Canadian institutionsnot available
Fundersnot available
KeywordsIvory towerPoetryPoliticsEconomic JusticeSociologyTowerPsychologyAestheticsLiteratureArtHistoryPolitical scienceLaw

Abstract

fetched live from OpenAlex

Using a series of poetry conversations, the authors give voice to their experiences of the doctoral process to illuminate the emotional and affective-political experience, and engage with the neo-liberal powers of the doctoral journey. They write poems to remember the body, and bring justice to the many bodies that have experienced the chill inside the “ivory tower.”

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)0.009
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.019
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0190.035
Scholarly communication0.0150.010
Open science0.0010.009
Research integrity0.0030.013
Insufficient payload (model declined to judge)0.0030.002

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 head0.407
GPT teacher head0.616
Teacher spread0.209 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations4
Published2018
Admission routes1
Has abstractyes

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