Nature or nurture? Agency life‐cycles as a function of institutional legacy, political environment, and organizational hardwiring
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 A growing body of literature attempts to explain the life‐cycles of public sector organizations. Of particular interest have been the form and incidence of their birth and termination, and connecting these events to such variables as legal status and political ideology. Less attention has been given to the effect of intermediary life‐cycle events, the tasks performed by agencies, and their policy domains. This study builds on existing fixed characteristics (nature) and dynamic environmental (nurture) approaches and uniquely supplements them with a new institutional legacy paradigm that examines how previous organizational reforms influence future reform. Moreover, we advance existing studies by providing more comprehensive tests of the role that task type and policy domain play. Finally, we retest “classic” nature and nurture variables, namely, political turnover and legal form. Results suggest that nature and nurture provide important pieces of the organizational life‐cycle puzzle and that nurture comprises both external and intra‐organizational dynamics.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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