Processo de transferência de tecnologia entre universidade-indústria por intermédio dos núcleos de inovação tecnológica
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 research aims to analyze the process of transfer of technology between Industries and Public Universities, specifically at Innovation and Technology Centers (known as NIT in Brazil), as well as analyze the technology transfer in Brazil. The methodology was characterized as exploratory and descriptive, being constituted as applied, and conducted as a case study at one of the surveyed NITs. At first data were collected at the National Institute of Industrial Property (INPI), Brazilian Central Bank (BCB), Directories and Research Groups of the National Council of Technological and Scientific Development (CNPq). NITs in Parana State were subsequently surveyed through Octagon Innovation methodology and semi-structured questionnaires designed to collect data. Brazil is getting technology from major economic powers like the United States, Germany, Japan, France, Italy, UK, Switzerland, Canada and Spain, with a considerable increase even after the economic crisis which began in 2008. Meanwhile Brazil has exported more technologies than imported them in the last 12 years. Barriers to cooperation between universities and industries are still very present. There are currently 27,523 research groups in all areas of knowledge, but only 0.31% of them develops activities related to technology transfer, and 58% do not establish relationships with industry. Through the diagnostic tool, octagon innovation, it was possible to verify the scenarios of core technology innovation of public universities in the state of Paraná. It was possible to identify such Center has a team of professionals with excellent level of training and different training areas, but it is experiencing difficulties in establishing internal relationships among members and other teachers and university research groups. Difficulties were also found in the process of developing external contacts, including establishing new networks of researchers, students, other universities and even leaders in the productive sector to generate and refine new ideas in order to prevent internal failures to processes. Among the five surveyed NITs, only one, got better results being the best in the state (NIT 1). Through research, it was found that the NIT 1 studies and implements mechanisms which transform knowledge into innovation. Its work aims to contribute to the scientific, technological and socioeconomic Brazilian society. However, it is possible to detect problems since technology depends on the process of technological diffusion, adoption of technology by society through continuous learning, enabling increased performance of services, processes and products produced in the market.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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