Bibliographic record
Abstract
This research paper focuses on strengthening program management protocols, which can help in mitigating nuances along with duplication, and redundancies. In this context, seven components have been considered for facilitating the achievement of sustainable management of a development program. Thus, for conducting this study, a conceptual framework of the “CARROT-BUS” model has been taken into due consideration. CARROT mainly stands for Capacity, Accountability, Resources, Results, Ownership, and Transparency, which emphasizes enabling the environment while BUS is perceived as a bottom-up strategy. Correspondingly, this holistic and causal model can be considered to be conceptually synonymous with Abraham Maslow’s hierarchy of needs theory. Additionally, each step of the model needs to be well-defined and described. Hence, designing and implementing sustainable development programs can be considered to be complex. Therefore, the systems presented in this abstract are a way of addressing these complexities. Herein, for conducting this study, secondary sources have been taken into high consideration. The use of these sources has significantly assisted in enhancing the existing knowledge on the identified issue in detail. Thus, the study has been able to understand the importance of sustainability in the present scenario, especially in project management. Based on the overall findings, it can be stated that sustainability is one of the key aspects, which are maintained by organizations all around the world for attaining success.
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 | 0.013 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".