Compte rendu: Unveiling the Depths of Social Innovation: A Journey Through Scholarship and Critique. A review of The Encyclopedia of Social Innovation
Bibliographic record
Abstract
It is unclear when, how, or by whom the term “social innovation” was first used. According to Moulaert et al. (2013), the term was coined in Europe in the 1960s. The first book on the subject was published in 1967 by Fairweather, who sought to address social problems through experimental methods and had a reformist and moralistic view of sociology. In Latin America, the terms “appropriate technology” (Caldas & Alves, 2013) and “tecnologia social” (Pozzebon, Souza & Saldanha, 2023) emerged around the same time. These terms were aimed at social development and questioned the role of technology in society, proposing an emancipatory view to create spaces and opportunities that redefine social relations. The term’ social innovation’ has garnered substantial attention in recent academic and empirical research. This is evident in the proliferation of events, exhibitions, and platforms dedicated to discussing and promoting social innovations. The term has also become a prominent keyword in English language scientific research, particularly in business administration, public administration, and public policies, where it supports a wide range of theoretical and ideological positions on the nature of innovation in contemporary society. [...]
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.014 | 0.022 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".