Thriving in the future: intentional followership development
Bibliographic record
Abstract
Purpose The purpose of this paper is to highlight the significance of the role of followership by raising self-awareness of those in organisational hierarchies through the followership intelligence activity. As practitioners, we intentionally spotlight the importance of followership learning and link followership development to the future needs of a thriving organisation through the facilitation of our activity. Design/methodology/approach This paper outlines the proposed followership intelligence activity (FIA), which includes a progression of questions, group discussions and linkages to adult learning principles, experiential learning and followership theory. Findings Feedback from authors’ workshops and general observations indicate that once “learning” leaders understand the importance of followership and identify as both followers and leaders, they begin to build and promote work environments open to conversations about the behaviours and skills of exemplary followers. Practical implications People cannot change behaviour that they do not notice. However, when leaders begin to identify as both leaders and followers, their openness to learning, developing (self and others) and having followership conversations increases, which promotes both personal awareness and growth. As leaders model and create conversations about exemplary followership skills, they can promote and inspire these behaviours in others within the organisation. Originality/value The intention of embedding the FIA into our leadership development programme is to legitimise, honour and promote life-long learning of both leadership and followership. Both roles are vital for a thriving workplace, and they need to be performed with strength, accountability and pride.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".