The realistic downsizing preview: a multiple case study, part I: the methodology and results of data collection
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
While downsizing has become an increasingly popular organizational tool in the achievement and/or maintenance of competitiveness the negative side effect known as survivor syndrome continues to plague many post‐downsizing organizations. This article series examines the full spectrum of research with the goal of producing a model. The model is based upon the problems survivors’ experienced and modeled after the realistic job preview. The realistic downsizing preview (RDP), which can be effectively used before the downsizing, is implemented to prevent survivor syndrome. This two‐part article is an exploratory study intended to produce an instrument, the RDP. This will be tested utilizing a cross case study analysis of nine major North American organizations. The first part re‐introduces the RDP then concentrates on the methods of data collection and initial presentation of results from the nine case studies that were used to develop and refine the model.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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