Trading Away Women’s Rights: A Feminist Critique of the Canada–Colombia Free Trade Agreement
Bibliographic record
Abstract
Summary The internal conflict in Colombia has resulted in documented violations of human rights and international humanitarian law. In particular, Colombian women and their human rights have been disproportionately impacted by the conflict. It is within this context that the Canada-Colombia Free Trade Agreement (CCFTA) is being proposed, and there is serious concern that Canadian investors could perpetuate the violence or become complicit beneficiaries of human rights violations in Colombia once the CCFTA is ratified. Against this background, this article takes a feminist approach to international investment law to demonstrate that international investment agreements (IIAs) and free trade agreements with investment provisions (FTAs), such as the CCFTA, maintain and reinforce gender hierarchy to the detriment of women’s socio-economic rights, needs, and interests. By engaging in a feminist critique of the CCFTA’s provisions on non-discrimination, performance, expropriation, corporate social responsibility, reservations, investor-state arbitration, and general exceptions, as well as the labour side agreement, the ramifications of international investment law on Colombian women’s rights and women’s rights generally becomes apparent. In order to remedy these shortcomings, recommendations are made to alleviate the potential strain of international investment law and the CCFTA specifically on women’s rights.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.021 | 0.024 |
| Scholarly communication | 0.013 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".