Knowledge Accumulation within an Organization
Bibliographic record
Abstract
We develop a simple model of task allocation for knowledge workers over their career within an organization. The human capital theory initiated by Becker (1962, 1964) has offered a rich analysis of an individual’s life cycle investment in human capital. One of the main result of this literature states that human capital investments are undertaken at the early stage of the career because workers have then a longer period of time over which they can benefit from the return of their investments. In this paper, we consider a knowledge accumulation problem within an organization that cannot prevent the worker from quitting and using the knowledge outside the organization. In the first best situation, we show a similar result as in the human capital theory, i.e. the share of time allocated to knowledge creation tasks decreases over time. We then ask how this pattern is affected when the knowledge worker can leave the organization and benefit from this knowledge outside the organization. In this case, we obtain the novel result that the time path of the fraction of working time allocated to knowledge creation tasks is non-monotone. This fraction is highest at the early career stage, falls gradually, then rises again, before falling finally toward zero. We also show that an increase in the firm-specificity of knowledge can increase or decrease the life-time income of the knowledge worker.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".