Bibliographic record
Abstract
The economic slump that the Western world is in will last for a generation unless and until serious changes are made. While we have been through this scenario before, this time it’s different. The economy is not expanding – it’s flatlining – and the conventional solutions are doing little more than placing us in survival mode. Economic strain brings challenges, but it also provides opportunities for meaningful reform that takes into account the economic realities we are faced with today. As a specialist in economic growth theory, I have found the upheavals over the past half century to be especially compelling. Even more intriguing is where this has left us in recent years. Since the end of the Second World War, we have experienced several major recessions in the developed world (“Economic Growth since WWII” n.d.). Throughout those times, government policy was reasonably effective in doing what had to be done to get the wheels turning. Lowering interest rates spurred consumption of big-ticket items. The combination of lower taxes and higher spending helped return us to full employment. The idea was that if you just gave the system a slight nudge, things would pretty much take care of themselves. To put it bluntly, that model doesn’t work now, and is broken beyond being fixable. Public policy has placed us in a low-economic growth box that will go on for an extended period that will be impossible to sustain. This has profound implications for all industries; however, it is particularly acute for healthcare. From 1998 to 2008, annual spending increases averaged about 7.5%. In 2011, it was estimated to be closer to 4% (Canadian Institute for Health Information 2011). Is this because there’s less of a need to spend? Of course not. It’s all about ability. When the economy is stagnant, it becomes a zero-sum game – if you want to spend a dollar on healthcare, it must be at the expense of something else. In order to understand why we are engaging in a very different discussion than at any other time in economic history, we need to look at the factors that brought us here. Let’s start with some factors that weren’t in play in the past recessionary rounds:
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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.015 |
| Scholarly communication | 0.010 | 0.022 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.007 | 0.020 |
| Insufficient payload (model declined to judge) | 0.028 | 0.008 |
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".