General Purpose Technologies and Productivity Surges: Historical Reflections on the Future of the ICT Revolution
Bibliographic record
Abstract
Presented to the International Symposium on ECONOMIC CHALLENGES OF THE 21ST CENTURY IN HISTORICAL PERSPECTIVE, Oxford, England, 2nd-4th July, 1999 Celebrating the Scholarly Career of Charles H. Feinstein, FBA. Re- examination of early twentieth century American productivity growth experience sheds light on the general phenomenon of recurring prolonged swings in total factor productivity (TFP) growth rate experienced in the advanced industrial economies. After a “productivity slowdown” lasting more than a quarter of a century (during which TFP for in the manufacturing sector grew at less than 1 percent per annum, industrial TFP surged to average 6 percent per annum during 1919-29. This contributed substantially to the absolute and relative rise of the US domestic economy’s TFP residual, and in many respects it may be seen as the opening of the high-growth era that persisted into the 1970s. The productivity surge marked the culminating phase in the diffusion of “the dynamo” as a general purpose technology (GPT); that saw a shift in the underlying technological regime brought about by the implementation of critical engineering and organizational advances originating in some two decades earlier. Closer analysis reveals the significant concurrence of the factory electrification movement in this period with important structural changes that were taking place in US labor markets; in addition, there were significant complementarities between managerial and organizational innovations and the new dynamo-based factory technology, on the one hand, and, and the reinforcement of both kinds of innovation by the macroeconomic conditions of the 1920s. This more complicated, historical view of the dynamics of GPT diffusion is supported by comparisons of the US experience of factory electrification with the developments taking place in Japanese industry during the 1920’s, and in the UK manufacturing sector during the 1930’s. Concluding sections of the paper reflect on the analogies and contrasts between the historical case of a socio-economic regime transition involving the electric dynamo and the modern experience of the information and communications technology (ICT) revolution. Our formulation the GPT concept in explicitly historical terms contributes to explaining the paradoxical phenomenon of the late twentieth century productivity slowdown in the US. It also points to some contemporary portents of a future phase of more rapid ICT-based growth in total factor productivity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.004 | 0.012 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".