Identity leadership going global: Validation of the Identity Leadership Inventory across 20 countries
Bibliographic record
Abstract
Recent theorizing applying the social identity approach to leadership proposes a four‐dimensional model of identity leadership that centres on leaders’ management of a shared sense of ‘we’ and ‘us’. This research validates a scale assessing this model – the Identity Leadership Inventory ( ILI ). We present results from an international project with data from all six continents and from more than 20 countries/regions with 5,290 participants. The ILI was translated (using back‐translation methods) into 13 different languages (available in the Appendix ) and used along with measures of other leadership constructs (i.e., leader–member exchange [ LMX ], transformational leadership, and authentic leadership) as well as employee attitudes and (self‐reported) behaviours – namely identification, trust in the leader, job satisfaction, innovative work behaviour, organizational citizenship behaviour, and burnout. Results provide consistent support for the construct, discriminant, and criterion validity of the ILI across countries. We show that the four dimensions of identity leadership are distinguishable and that they relate to important work‐related attitudes and behaviours above and beyond other leadership constructs. Finally, we also validate a short form of the ILI , noting that is likely to have particular utility in applied contexts. Practitioner points The Identity Leadership Inventory ( ILI ) has a consistent factor structure and high predictive value across 20 countries and can thus be used to assess a leader's ability to manage (team and organizational) identities in a range of national and cultural contexts. Identity leadership as perceived by employees is uniquely related to important indicators of leadership effectiveness including employees’ relationship to their team (identification and perceived team support), well‐being (job satisfaction and reduced burnout), and performance (citizenship and innovative behaviour at work). The ILI can be used in practical settings to assess and develop leadership, for instance, in 360‐degree feedback systems. The short form of the ILI is also a valid assessment of identity leadership, and this is likely to be useful in a range of applied contexts (e.g., those where there is a premium on cost and time or when comparing multiple leaders or multiple time points).
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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 | 0.017 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".