Bibliographic record
Abstract
Markets are assumed by the logic of capital budgeting to be homogeneous. For this reason, differences in market structures, scale, complexities, connectivity, and administrative approaches are assumed to be value neutral or inconsequential. This chapter illustrates that these factors influence the sequencing of commitments and shows the differing impacts they have on a firm’s performance (or policy outcomes). When market structures and competition are considered, monopolists tend to defer commitments until the option premium is significantly high, in the absence of pre-emption threats. However, increasing competition encourages firms to exercise early in order to lock in payoffs that could otherwise be lost to rivals—a classic prisoner’s dilemma. Managerial capabilities differ according to the strength of subsidies’ rent-extractive bias, through the exercise of strategic choices. Managers abdicate their technology choices decisions to policy under regimes of generous subsidies. Carbon taxation uses pricing signals to influence the types or mix of supplies that managers may eventually choose. Two policy experiences are examined: Australia’s failed programme is contrasted with Canada’s relatively viable experiments in British Columbia.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".