Bibliographic record
Abstract
<p>An ebullient global campaign against investment in fossil fuel industries isattracting a diverse entourage that includes community activists, universities andeven some mainstream financial institutions. The movement is coagulatingaround anti-fossil fuel networks, such as 350.orgs Fossil Free, and the FossilFuel Divestment Student Network as well as numerous local hubs of activismsuch as Divest Harvard and Fossil Free UNSW. Frustrated by governmentprevarication, the campaign avows to curb greenhouse gas emissions bypressuring investors to shun fossil fuel industries such as oil firms and coalminers in the hope that they adopt more environmentally benign practices or goout of business altogether. Divestment conventionally means withdrawingfinancial ties from a company, usually by selling stocks or bonds, but mayextend to other financial sanctions such as a bank declining a loan.</p><p>The foregoing campaign is opposed by many financiers, and governmentstoo, for reasons that include the belief that divesting is financially irresponsible,it cannot leverage positive change and that it is unlawful or legally dubious. TheBritish government in February 2016 warned municipal councils against fossil fuels divestment and threatened to financially punish those who defy it. Anumber of United States universities, which have faced concerted pressure fromstudents to divest, have similarly resisted for the foregoing reasons. The legalcontext is ambiguous, partly because of the paucity of case law or legislativeguidance on whether and how climate change risks and impacts can be criteria infinancial decision-making. Legal opinions tend to be couched with manyqualifications, such as one given to the Interfaith Center on Corporate SocialResponsibility the leading faith-based investor network in the United States that the law likely preclude[s] a fiduciary from eliminating the entire [fossil fuel]industry [from its portfolio] without considering each investment [that would beaffected] on a case-by-case basis.</p><p>This article assesses the legality of fossil fuels divesting. Divesting is a formof socially responsible investing (SRI), and therefore the analysis draws onunderstandings of SRIs legal context. The article focuses on the majorAnglophile jurisdictions because they are either globally preeminent financialmarkets (United States (US) and United Kingdom (UK)) or host large fossilfuel sectors such as oil sands (Canada) and coal mining (Australia). Thediscussion is not directly applicable to civil law systems, such as Germany orJapan, where some different legal doctrines and procedures govern investing.Neither the merits of fossil fuel investing nor its impact on corporate behaviourare assessed: the focus is strictly on understanding the legal scope to practisefossil fuels divestment.</p>
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.
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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".