The Social Identity Approach to Leadership: The Case of Alberta
Bibliographic record
Abstract
The study of political leadership within the discipline of the political science has recently grown into a large, complex, and insightful literature. However, the extensive number of concepts, theories, and frameworks developed by international leadership scholars have been underutilized when it comes to developing further understanding of political leadership in the Canadian context. This thesis attempts to address this gap by focusing on the process by which individuals are selected to be leaders. I utilizes social psychology and Identity Leadership Theory to theorize that leaders are successful to the extent that are able to cohere with broader group processes by articulating group characteristics, establishing individual prototypicality, and entrenching their policy agenda in pre-existing collective identities and understandings. The study develops and examines a concise causal relationship and hypotheses through a case study of the Albertan provincial context. This comprises analyses of two premiers, William Aberhart and Peter Lougheed, that utilize a set of primary communicative sources to examine the substantive components of their successful leadership appeal. Overall, this thesis’s findings suggest that these leaders were successful despite not meeting the expectations of the analysis’s hypotheses. Consequently, it is concluded that Identity Leadership Theory is not an accurate or useful means by which to understand political leadership in Canada.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.030 | 0.011 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".