Bibliographic record
Abstract
Reviewers have the benefit of hindsight. This is especially true of the present review of four books concerning retirement and pension policy, all of which were penned prior to the crisis that depressed global equity markets in the last quarter of 2008 and continued to plague markets throughout 2009. The current crisis suggests that post-Enron and current Sarbanes-Oxley economies in the US are apparently not that different from pre-Enron and pre-Sarbanes-Oxley economies. Hence, it is clear that the post-Enron but pre2008/2009 crisis calls for more stringent government oversight and better shareholder activism did not produce the intended results. We may ask ourselves therefore: what is to be gained by suggesting more of the same kinds of policies? Of course, one can argue that the policy prescriptions brought on by the corporate scandals that began the decade were not properly implemented or adhered to thoroughly enough. But maybe, just maybe, there are more fundamental problems with capitalist economies that demand a more critical and radical analysis to unearth. When will we finally stop being surprised by economic collapses, poor outcomes for labour, and the failures of state policy? review essay / note critique
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 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 | 0.006 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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".