Bibliographic record
Abstract
Successfully navigating the public policy landscape of the 21st century is becoming an essential pre-requisite for businesses operating in a national and global environment. Public policy plays a key element in defining the operational parameters within which businesses can succeed or fail. The reason being that in the process of formulating and implementing their public policy response to the contemporary hot button issues, governments are also defining the microeconomic landscape and shaping the business environment within which businesses operate. The global financial crisis of 2008 triggered the Great Recession. The financial contagion effect impacted severely on national and multinational corporations, most national economies, triggered massive unemployment, created social tensions and revealed the limitations of the contemporary economic governance architecture. The public policy dilemma faced by most countries has been textured by two cataclysmic events- the global financial crisis and the Great Recession. These events have triggered an epic economic debate. On the one side are the proponents of fiscal austerity in order to combat fiscal deficits. On the other side are the advocates of a fiscal stimulus that will contribute to economic growth. Developing a potent business strategy under these policy options is a challenge for all national corporations and most global enterprises. The current and near future business environment is best described as being uncertain and volatile. This is compounded by the current business climate which is defined by a weak consumer sector, slumping natural resource prices and stumbling national economies such as that of China.
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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.033 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.012 | 0.010 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".