Bibliographic record
Abstract
Management is a familiar term but difficult to be discerned in today's organizations.Every individual has a different understanding of the management and the tasks assigned to a manager.But, the managers' duties cannot be limited to several specific tasks.One of the important duties assigned to the managers in organizations is the identification of the potential talents of the staff members and this task, accomplished perfectly, paves the way for an enhancement in the productivity.Individuals' performances are a function of their competencies and motivations.Since the human beings play key role in development and the actualization of development which is carried out by the hands of the human individuals, the satisfaction of the mental and psychological needs of the individuals is of a primary importance.The topic of human force motivation is among the issues in need of particular attention by the organizations' management.Due to the same reason, this significant issue was investigated in the present study so as to evaluate the motivation factors for the accountants.Accordingly, the study population of the present study was selected from the professors and the students of this field.After doing statistical tests by taking advantage of a combined method comprised of Entropy Shannon and Fuzzy Delphi technique, a comparison was run on the data collected from the questionnaires regarding the most important scales from the perspective of the professors and the students and tables were prepared, resultantly.The independence and the integrity of the occupations and the educational systems are the most critical scales of development, but, from the university students' perspectives, encouragement, attention and expressing gratitude after a job is accomplished and the provisioning of the growth and development opportunities were among the most important factors.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.959 | 0.937 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".