Relationships between Organizational Factors and Political Behaviour Tactics in the Islamic Republic of Iran: Kerman Province
Bibliographic record
Abstract
The organizations try to achieve their goals through using resources such as material and human resources, but most of them are a little successful to achieve their goals, however it is difficult to use the resources in order to achieve to personal and group gains that occur in the organization repeatedly. These actions called as political behavior include activities that go forward in order to work in the people or groups to obtain the protecting the personal gains when there are opposite solutions. In the present paper, the researcher studies the relationship between the organizational factors and the political behaviors or the policy in the Kerman's governmental organizations. This study to be done by juncture studies and correlative way in the population includes 1992 samples of the Kerman’s governmental organizations personnel and classified random sampling that include 322 samples. The researcher uses two questionnaires in order to gather the date and consult with the professors in order for determining the reliability questionnaires and evaluates them through re-examining and finally analyzes the collected data by means of software”SPSS
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".