Exceptional big linkers: Dutch evidence from the 20th century
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
This article investigates the effects of individual directors for corporate strategies and firm performance over the course of the 20th century for Dutch exchange-listed firms. We apply a multi-method approach on directors with many executive and supervisory roles in multiple firms – so-called big linkers. We first identify exceptional big linkers, board members whose presence is systematically related with firm characteristics. Our approach allows us to identify a number of exceptional individuals who were previously overlooked by business historians. Then we investigate the backgrounds of these exceptional big linkers. We find that their biographies and other archival materials provide explanations for their systematic relation with corporate outcome variables such as performance, debt and investments. Using additional information about these directors, including network centrality, bank relations and family histories, we are able to shed light on the multitude of explanations for the roles of exceptional big linkers.
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 | 0.000 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.005 |
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