Bibliographic record
Abstract
Cornelia Opoku Gyemfi is an LLM Candidate at Dalhousie University Schulich School of Law. Her area of specialisation is Maritime and Environmental Law. She received her LLB education in Ghana from Kings University College (Degree awarded by the University of Cape Coast). She completed her national service (a requirement under the Government of Ghana for undergraduates) with the Office of the Attorney General and Minister for Justice, Ghana. She spent all her summer vacations interning with reputable law firms in Ghana such as AB & David and Blay and Associates.\nAs a coursework based LLM student, she has taken courses in Maritime Law and International Law of Trade and Shipping and has written research papers in both courses. Subsequently, she intends to take courses in Intellectual Property Law, Oil and Gas Law, and Environmental Law.\nShe hopes to be able to practise as a lawyer in Canada and to someday go back home to Ghana and help develop the maritime and environmental legal regimes. The curiosity in knowing that there were laws that govern the sea when Ghana had impounded an Argentine Navy Ship at its Tema Harbour ignited an interest in Maritime Law for her. The issue of plastics disposal and pollution has been long standing in Ghana. About 80% of its pollution in the sea is caused by plastics which are not biodegradable. The combination of Maritime and Environmental Law offered her the unique opportunity to be an expert in both fields she is passionate about.\nShe chose Dalhousie first because of its location, being situated in Canada which is one of the most cosmopolitan countries in the world today. Being internationally recognized for excellence in marine and environmental law teaching and research, with one of the world's most extensive course offerings in marine and environmental law, she was convinced that it was the right school for her as such a sterling opportunity will nonetheless place her on the pedestal to achieving her career objective and go come back home to influence a positive change.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.040 | 0.039 |
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; both teacher heads agree on what is shown here.
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".