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Record W2072231234 · doi:10.12735/ier.v2i4p26

A Subjective Academic Narrative Reviewing Academic Collegiality

2014· article· en· W2072231234 on OpenAlexvenueno aff
Josie Arnold

Bibliographic record

VenueInternational Education Research · 2014
Typearticle
Languageen
FieldPsychology
TopicMentoring and Academic Development
Canadian institutionsnot available
Fundersnot available
KeywordsCollegialityNarrativePedagogySociologyPsychologyMathematics educationArtLiterature

Abstract

fetched live from OpenAlex

This paper is based upon a conceptual approach to making a scholarly addition to the privileged academic discourse. This paper develops the methodology of a subjective academic narrative to address the issue of academic collegiality that is being explored. This methodology involves a journey of intellectual enquiry into the work of the self as data. This subjective academic narrative is a response to the research question: 'in today's world of the subjective self and online interactions is collegiality possible or even desirable?'. The conceptual approach of this paper involves constructing a personal narrative arising from experience and reviewing academic literature regarding the possibly inherent discordance between collegiality and personal career development. The core business of the university may well be teaching undergraduate students, as this brings in the most sure and significant income, but if you want to get up the academic scale, you must also excel at the various demands of the promotions regulations. These involve proof of collegiality as well as personal aspects of teaching and learning, research, and management of courses, people and discipline areas. This paper explores whether or not such interactions are possible.

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)0.006
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.432
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.004
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 science0.0010.000
Research integrity0.0000.002
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 head0.195
GPT teacher head0.547
Teacher spread0.351 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2014
Admission routes1
Has abstractyes

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