Development and testing of an assessment model for social enterprises
Bibliographic record
Abstract
Purpose – The trend toward the indiscriminate use of natural resources and social decay has widened the gap between social classes, rich and poor, leaving the poorest unprotected. This situation, with the current financial crisis has also led to the creation of social organizations by the people in the highest levels of marginalization, through which they sell products manufactured by themselves and support enhance the economy and enhance a better quality of life for themselves. The paper aims to discuss these issues. Design/methodology/approach – A major development for growth of these organizations is the existence of responsible consumerism. Thanks to the technological advancements and the mass distribution of information, and the supply chain, the world population is beginning to get aware and becoming concerned by the effects of the hyper-consumption culture currently prevailing. Findings – The existing models of national indices based on consumer opinion and satisfaction merely include the characteristics of the products and services offered, but do not include variables that aid in determining their impact on a social enterprise. This research aims to fill that gap. Originality/value – The paper shares the results of a qualitative and quantitative survey performed during the first half of 2014 using a model of structural equations developed to test new hypotheses that include a variable which has been called “social responsibility.”
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 | 0.007 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".