MétaCan
Menu
Back to cohort
Record W3090789781 · doi:10.5430/bmr.v9n3p46

Research Methods: Issues and Research Direction

2020· article· en· W3090789781 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.

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

VenueBusiness and Management Research · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Marketing Education
Canadian institutionsnot available
Fundersnot available
KeywordsRelevance (law)Higher educationQuality (philosophy)Business educationReliability (semiconductor)CurriculumKnowledge managementPlan (archaeology)Data collectionField (mathematics)Business analysisEngineering ethicsSociologyManagement scienceComputer scienceBusinessMarketingBusiness modelPolitical sciencePedagogyEngineeringSocial science

Abstract

fetched live from OpenAlex

This paper proposes a research plan to investigate the research methods issues (i.e. research design, sampling methods, data collection methods, data analysis techniques, measurement scales, and reliability/validity tests, among others) used in business students’ thesis/dissertation works in institutions of higher learning. Specifically, the proposed research aims to help in understanding the dominant research methods used by thesis/dissertation research students in the field of business management in institutions of higher learning, shed light on possible relevant research methodology issues in business management education and proffer managerial and theoretical recommendations that will assist research methodology in business disciplines in institutions of higher learning. Among other things, the proposed investigation is expected to help in assessing the quality and relevance of business research works in higher institutions; assist in repositioning business education curricula to align with academic, regulatory and industry expectations; improve the quality and relevance of research works undertaken in business schools in institutions of higher learning; and stimulate research in cognate areas.

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)0.022
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.768
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0220.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0000.001
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 head0.217
GPT teacher head0.483
Teacher spread0.266 · 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