Coopetition at Society Level: A Scale Validation
Bibliographic record
Abstract
The researchers study coopetition in various levels such as individual, intraorganizational or interorganizational. However, there is a gap in coopetition studies at the society level, at the meta-level. We consider Social Coopetition as the capacity of the society's stakeholders to work together, oriented to create social value to generate solutions to economic, social and environmental problems, providing local development based on cooperation and social commitment. This research has twofold objectives, i) to define Social Coopetition and propose its dimensions, ii) to validate a scale to measure coopetition at society level. An expert's panel analyzed 101 variables extracted by the literature review, and they selected 75 variables grouped in 7 dimensions as a qualitative pre-validation. In the sequence, we performed an exploratory and confirmatory factor analysis to validate the scale. Our findings indicated 12 dimensions could express the social coopetition level: social asymmetry, perceptions of individual and collective benefits, socio-political characteristics, communication, competition, social competence, social commitment, previous experience, social governance, interdependence, technological and innovation level and cultural similarity. The findings provide a scale to monitor the social coopetition through 48 variables. Our results bring a novel in the coopetition field and have theoretical and practical implications. The findings explore a new coopetition level. Also, it provides a tool for municipal management to improve the coopetition strategies performance toward the generation of social value.
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.
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 | 0.030 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".