Exploring the perspectives of leaders and followers on implicit beliefs (both traits and roles) about followers
Bibliographic record
Abstract
Purpose This study explored beliefs about the follower role by comparing leader and follower responses. The purpose was twofold: first, to investigate the implicit follower beliefs and role orientations of leaders and followers in a single study; second, to correlate two implicit belief instruments: the implicit followership scale and the coproduction and passive role orientation scale. Design/methodology/approach This research used a non-experimental, quantitative methodology to test four research questions. Data were gathered by surveying leaders and followers from Canada and the United States. Descriptive and inferential statistical techniques were used to analyze the study data and answer the research questions. Findings The study’s results showed a small statistical significance between the two instruments: IFT antiprototypes correlate to and predict assumptions about passive follower orientations. Research limitations/implications The study contributed to the followership, IFT, and role orientation literature, addressed several research gaps, and provided several avenues for future research. Practical implications The study provides valuable insights and actionable knowledge for individuals, teams, and organizations. Individuals who understand their implicit follower beliefs and role orientations can use this knowledge to understand their workplace behavior and interactions with others. Originality/value This research was the first to report on the IFTs and follower role orientations of leaders and followers in the same study and correlate two popular implicit belief scales.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".