Globalization Across the Disciplines: A Comparison of the Teaching of Globalization in Commerce and Global Development Studies at Queen’s University
Bibliographic record
Abstract
It is often said that we are living in the "age of globalization." This research questions what is meant by this statement. The inquiry is divided into two areas of research. The first part is a review of the academic literature on globalization. Globalization was found to be a term used across a wide variety of disciplines. However, there is no consensus between the disciplines on what exactly the term encompasses. This led to the second area of research: Investigation of the teaching of globalization at Queen's University. For the scope of the research, undergraduate Commerce and Global Development Studies students were chosen. Students from either discipline filled out a survey on globalization and how it is taught at Queen'sUniversity. The results strongly indicated that the students in Commerce and Global Development Studies had very difference conceptions of globalization and were taught about it very differently. The larger implications for what the research findings suggest are discussed University and beyond, while also acknowledging the limitations of the scale of the research. The inquiry concludes with suggestions for moving forward, including further research and alterations to the teaching of globalization at Queen's.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.008 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".