<b>Research Note</b>—Investments in Information Technology: Indirect Effects and Information Technology Intensity
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
Many studies measure the value of information technology (IT) by focusing on how much value is added rather than on the mechanisms that drive value addition. We argue that value from IT arises not only directly through changes in the factor input mix but also indirectly through IT-enabled augmentation of non-IT inputs and changes in the underlying production technology. We develop an augmented form of the Cobb-Douglas production function to separate and measure different productivity-enhancing effects of IT. Using industry-level data from the manufacturing sector, we find evidence that both direct and indirect effects of IT are significant. Partitioning industries into IT-intensive and non-IT-intensive, we find that the indirect effects of IT predominate in the IT-intensive sector. In contrast, the direct effects of IT predominate in the non-IT intensive sector. These results indicate structural differences in the role of IT in production between industries that are IT-intensive and those that are not. The implication for decision-makers is that for IT-intensive industries the gains from IT come primarily through indirect effects such as the augmentation of non-IT capital and labor.
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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 | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.013 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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