<i>I, We</i> , and <i>They</i> : A Linguistic and Narrative Exploration of the Authorship Process
Bibliographic record
Abstract
Abstract Introduction While authorship plays a powerful role in the academy, research indicates many authors engage in questionable practices like honorary authorship. This suggests that authorship may be a contested space where individuals must exercise agency --a dynamic and emergent process, embedded in context--to negotiate potentially conflicting norms among published criteria, disciplines, and informal practices. This study explores how authors narrate their own and others’ agency in making authorship decisions. Method We conducted a mixed-methods analysis of 24 first authors’ accounts of authorship decisions on a recent multi-author paper. Authors included 14 females and 10 males in health professions education (HPE) from U.S. and Canadian institutions (10 assistant, 6 associate, and 8 full professors). Analysis took place in three phases: (1) linguistic analysis of grammatical structures shown to be associated with agency (coding for main clause subjects and verb types); (2) narrative analysis to create a “moral” and “title” for each account; and (3) integration of (1) and (2). Results Participants narrated other authors most frequently as main clause subjects ( n = 191), then themselves ( I ; n = 151), inanimate nouns ( it, the paper ; n = 146), and author team ( we ; n = 105). Three broad types of agency were narrated: distributed ( n = 15 participants), focusing on how resources and work were spread across team members; individual ( n = 6), focusing on the first author’s action; and collaborative ( n = 3), focusing on group actions. These three types of agency contained four sub-types, e.g., supported, contested, task-based, negotiated. Discussion This study highlights the complex and emergent nature of agency narrated by authors when making authorship decisions. Published criteria offer us starting point--the stated rules of the authorship game; this paper offers us a next step--the enacted and narrated approach to the game.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".