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Record W2079985241 · doi:10.5539/ass.v7n4p2

Graduate Skills in Business Learning

2011· article· en· W2079985241 on OpenAlex
Tori Vu, Leigh Wood, Brendan Rigby, Anne Daly

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueAsian Social Science · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsnot available
FundersAustralian Government
KeywordsCurriculumGrading (engineering)EmbeddingSkills managementBusiness educationEngineering ethicsMathematics educationPedagogyMedical educationPsychologyHigher educationPolitical scienceEngineeringComputer scienceMedicine

Abstract

fetched live from OpenAlex

This article presents the background to a general increase in interest in developing the graduate skills of undergraduates in business in Australian universities. The change reflects the call from industry for greater emphasis on these skills; changes in the existing skills of students commencing a business education; and in the perceived role of universities in developing their students’ capacities. The aim of our project, “Embedding the development and grading of generic skills across the business curriculum” (EDGGS), was to develop new ways of successfully embedding these skills in the curriculum. This article outlines the research methodology and presents our project outcomes. The project has made a significant contribution to the development of readily accessible material for the embedding of generic skills in the business curriculum, as discussed in this and the other articles in this Issue.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.720
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.002
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 head0.066
GPT teacher head0.362
Teacher spread0.297 · 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