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Non-profit organizations (NPOs) play an important role in society. Nowadays, many companies apply the phenomenon—corporate social responsibility (CSR) which supports sustainable development and cooperation between the for-profit and non-profit sector. These companies are careful to cooperate with organizations and make decisions based on many factors, such as financial stability and independence of non-profit organizations. These attributes are assessed by predictive models. The models are a common tool in the for-profit sector compared to the non-profit sector. In our case, the main aim of the research is to propose a prediction model to estimate financial status of Slovak non-profit organizations using discriminant analysis. The overall sample consists of 351 NPOs dividing into training and testing sub-samples. We find that model classifies correctly almost 91% of NPOs in the training sample, respectively less than 80% in the testing sample. However, the results show that all vulnerable NPOs are correctly classified based on the testing sample.
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Stored only when both papers are in the corpus — 12 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.