A Comparative Analysis Career Drivers Marketing & Financial Professionals using RSI Psychometric Tool
Why this work is in the frame
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Bibliographic record
Abstract
The paper presents the authors’ own research, which points to the possibility of applying the Richmond Survey Instrument test on the two different profiles of employees (Finance & Marketing) in Pune region. Participants and procedure-The research was conducted in the years 2019-2020 in Pune. The study population comprised 100 individuals from both the profiles. The employees were selected by Non-Probability Convenience Sampling method. The research participants had never undergone psychological evaluation for personality test (for instance, they had never taken the RSI test). The study population comprised 133 males (66.5%) and 67 females (33.5%). Results The statistical procedures applied in the present study allowed us to conduct empirical examination of the indicators of the investigated variables constituting the major psychological criteria for describing psychological functioning of personality, and thus to identify the main Career Anchors of these two professionals. Analysis of the data obtained as a result of this research allowed us to distinguish two significantly different clusters in the group examined individuals. The results of the present investigation indicate that cluster 1 exhibited a higher level of Strong determination to the specific Career Anchors whereas of personality structure compared with the study participants belonging to cluster 2. Keywords: Richmond survey Indicator; Psychological; Career Anchors; Personality
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it