Innovation and collaboration in the geographic information systems (GIS) industry: evidence from Canada and the United States
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 paper examines the role of collaborative technical activity in the innovation performance of Canadian and US companies in the geographic information systems (GIS) industry. This young but rapidly growing sector produces specialised hardware and software for cartographic applications (computer mapping). Evidence from a sample of 384 companies suggests that innovation is strongly dependent upon in‐house R&D. The results also suggest that a firm’s propensity to operate within a collaborative network varies directly with its R&‐intensity. A description of the main benefits and costs of collaboration is presented. Although there is no statistical association between innovation and the incidence of external collaboration, the evidence suggests that R&D partnerships contribute to the innovation process in a number of important ways. The key contribution lies in the speed of product commercialisation. A related finding is that collaborators tend to generate radical innovations more frequently than less successful and/or non‐collaborators.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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