Bibliographic record
Abstract
Companies across the globe are embracing the open model, a trend that has been fueled by globalization and digitization. Firms increasingly rely on external staff as well as their permanent in-house employees to meet their business needs. flexibility of the model enables organizations to be more agile, react faster to new opportunities, and drive competitive advantage. But the shifting talent base also brings challenges, with new approaches to performance management, risk management, and decision-making required to meet them, according to New Ways of Working ... Managing the Open Workforce, a CGMA report based on a survey of more than 1,100 senior executives. [ILLUSTRATION OMITTED] The workforce is evolving into a mixture of full-time employees, contractors, freelancers, and, increasingly, people with no formal ties to your enterprise at all, Girish Bhat, FCMA, CGMA, the CFO of Gammon India, told researchers. You have to work with people who move more freely from role to role across the organization and across geographical boundaries. trend is most established in the Americas. Thirty-eight percent of respondents in the United States and Canada said that at least half of their workforce was made up of external talent, followed by 36% of those polled in Latin America. In Europe, this was the case for 27% of the companies represented in the survey, 21% in Asia, 17% in the Middle East and North Africa, and 14% in sub-Saharan Africa. shift looks set to continue over the coming years, with 45% of those in the United States and Canada and 36% of respondents in Latin America and Europe predicting that more than half of their workforce will be external in five years. Cost is considered to be the main benefit by leaders in Europe and North America, while respondents in Asia Pacific gave greater priority to the increased exposure to new ideas and specialist knowledge that the model brings, as well as improved organizational agility. CHALLENGES AND RISKS Managing a complex and constantly shifting network of employees, collaborators, and business partners also poses significant challenges. risk of data security breaches was of greatest concern to respondents, followed by disclosure of competitively sensitive information. potential for cultural mismatches and communication difficulties v among the workforce was a further issue highlighted in the study, while some respondents were worried about the effect on their organization's ability to make timely decisions. capacity to retain oversight and control over the performance and productivity of the external workforce is a significant challenge for managers. Of those polled, just 32.6% said that their company had struck the right balance between control and empowerment. key to achieving that balance is being able to articulate the vision of the organization very clearly to everyone, making sure that the staff are on board and that they understand the organizational goals, said Merike Henneman, CPA, CGMA, controller at Destination DC. …
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 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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.007 |
| Open science | 0.005 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".