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
ABSTRACT Subjectivity is an important element of employees' performance evaluations because its use can motivate employees and improve their productivity. Given this importance, it has been a prominent area of research within the management accounting literature. Using a structured approach, I review articles from 11 highly ranked accounting journals across 12 years with the objective of synthesizing and assessing the research to identify research gaps and opportunities for future research. I observe that two types of subjectivity are commonly studied: subjective performance measures and ex post discretion, across a wide range of settings. Research questions are investigated, drawing on theory from economics, psychology, and organizational behavior and using experimental, field study, survey, archival, analytical, and interview methods. My synthesis of the literature highlights many opportunities for future research to further the study of subjective performance evaluations. This study contributes to practice and accounting research by synthesizing and providing insights about the subjectivity literature as well as identifying opportunities for future research.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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