Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The purpose of this paper is to understand what are the best projections of these events effects on organizations and economies. The onset of the COVID-19 pandemic leads to a combination of economic and public health circumstances that challenge the accounting for and accountability of organizations that are mostly outside of their experience and that of academics for the past 50 years. Design/methodology/approach Through evidence-based policymaking research, evaluation and reporting tools the author draws on the extant research literature to develop estimates of likely effects of these events on organizations and economies. Findings The process of investigating this subject led the author to write a short research synthesis paper (Salterio 2020a) that summarized the historical economic evidence about the Spanish flu of 1918–1920 and various simulations of potential pandemic macroeconomic effects. This evidence allowed the author to quantify the potential effects of the crisis less than a month into the North American economic shutdown. Originality/value Using that research synthesis the author responded to the call for papers for this special issue by reflecting on the lessons that this crisis has for managers and organizations from both an accountability and accounting perspective.
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.
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 | 0.003 |
| 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 | 0.001 |
| 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 it