Benefit corporations in the valley of temples
Bibliographic record
Abstract
Benefit corporations have been introduced for the first time by the US State of Maryland, in 2010. Taking inspiration from it, other US States have regulated benefit corporations, as well as a number of foreign jurisdictions: among others, Italy in 2015. In brief, this is an opt-in model that a corporation may voluntarily choose, if it intends – alongside the pursuit of profits – to benefit also society and the environment. The primary aim of the work is to frame the benefit model and investigate whether (if so, to which extent) the balance among multiple competing interests may function. The focus is on Italy, but with a constantly looking at three other legal systems: the US (and its internal ramification), France and Canada. In addition, the work has a background aim: which contribution can the benefit model, framed as per above, give to the wider current debate on corporate purpose? Meaning the debate on the corporation as such, not just on voluntary models like the benefit one. To these ends, the work is divided into five chapters. Finally, the epilogue resumes the conclusions and explains the mythological metaphor employed in the title of the work (“in the valley of temples”).
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".