Impact of 360 Degree Feedback: A Follow-up study of Four Organizations
Bibliographic record
Abstract
A large number of organizations have been using 360 degree feedback in India as leadership development intervention. This paper is based on the feedback of 43 participants from four companies where the 360 Degree Feedback program was initiated. The study was done using a questionnaire method. The results indicated that there has been an overall positive impact reported of 360 Degree intervention on ones professional life after 360DF. More than 60% of the participants report that they visited 360DF data every quarter. 24 participants reported that about 50% of their action plans prepared at the end of the 360 intervention were implemented. At least 30% of the action plans were achieved by 6 of the participants and 2 participants reported achievement of all their action plans. The participants also reported that the RSDQ model based 360DF tool provided detailed insight covering various parameters of one’s role. The participants also recommend that with more periodic follow up and review sessions (every quarter) anchored by internal HR and more focus and seriousness among the participants to work on the action plans will result in using 360 DF for change and growth
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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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".