Mobilizing New Sources of Data: Opportunities and Recommendations
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
In June 2008, the U.S.-based website Glassdoor.com began posting anonymous company reviews and salary data from current and former employees of various organizations. Doing so not only brought to the world information that had hitherto been restricted to private circles, it spontaneously prompted some organizations to alter their workplace practices (Dineen & Allen, 2016; Dube & Zhu, 2021). At the same time, Glassdoor’s very activities gave rise to a completely new source of data for exploring a wealth of management and organizational phenomena (e.g., Bermiss & McDonald, 2018; Rhee, 2024). As this example illustrates, new data sources can not only transform managerial and organizational practices, they also invite the development of innovative theoretical explanations and can unlock opportunities to advance academic understanding of a broad range of management and organizational phenomena.
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 | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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