Technology development and transfer in the wake of the Paris agreement : international law for innovation in a polycentric climate governance system
Bibliographic record
Abstract
Since the adoption of the United Nations Framework Convention on Climate Change (UNFCCC) in 1992, States Parties to the international climate regime, in parallel to their emissions reductions objectives, have committed to take action to promote and cooperate in the development and transfer of technologies that control, reduce or prevent anthropogenic emissions of greenhouse gases. The Paris Agreement, which entered into force on November 4th, 2016, reaffirms this commitment. The specific manner through which States Parties to the Paris Agreement are to translate these commitments into action is however still being implemented. Indeed, significant developments in the governance structure for climate technology development and transfer (TD&T) are being implemented in order to further improve its functioning as part of the Paris Agreement’s bottom-up approach. An up-to-date understanding of these legal and policy tools is necessary to enable the different actors in the TD&T process, notably those from the private sector, to participate in this cooperative action to their full potential. In this context, the thesis addresses the following two main research questions. First, in the wake of the Paris Agreement, to what extent can TD&T contribute to the overall objective of the UNFCCC regime? Second, what are the legal issues surrounding the effective implementation of climate TD&T? By analyzing the legal issues linked to the implementation of TD&T in the evolving international climate governance landscape, the main objective of the research project is to determine to what extent improved understanding of UNFCCC law could contribute to effective implementation of climate TD&T. The research project posits that effective TD&T is an essential component to the achievement Paris Agreement’s overall mitigation goal. Its importance resides in its ability to contribute to developing country States Parties’ sustainable socioeconomic 3 development, as well as to encourage greater participation of non-state actors, such as those from the private sector. In order to answer its two research questions, the thesis first articulates its conceptualization of the Paris Agreement structure and of the role of law within it. It then focuses on TD&T to illustrate some issues at play within what it argues is an emergent polycentric governance system. It first does so by focusing on TD&T within the UNFCCC regime, before looking outwards to its interaction with other international legal and governance regimes. The analysis carried out in the thesis leads it to conclude that the normative basis for an improved contribution of TD&T to the UNFCCC’s overall objective is present in the Paris Agreement. Several questions however remain regarding the successful implementation of this normative basis.
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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 | 0.024 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.042 |
| Scholarly communication | 0.024 | 0.017 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.011 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".