Quid Pro Quo Authorship: Characteristics and Implications
Bibliographic record
Abstract
Quid pro quo authorship (QPQ) is a type of gift authorship in which authorship credit is exchanged in a mutually beneficial agreement. Such practices are considered to be unethical, but incentives to publish can nonetheless make QPQ appealing. Terminology to describe the QPQ phenomenon can differ across scholarly communities, making a thorough analysis of the attention to QPQ difficult. This article uses content analysis to conduct an in-depth examination of a corpus of scholarly literature on QPQ. This research seeks to ascertain information about the nature of QPQ and how it is perceived relative to other types of unethical authorship practices. Results support three defining characteristics of QPQ: mutual awareness, mutual agreement, and mutual benefit. Content analysis reveals two forms of QPQ: authorship-for-goods and authorship-for-authorship. Findings reinforce the notion that QPQ is a distinct form of gift authorship that is related to coercion authorship and honorary authorship. Implications for the scientific enterprise, academia, and society are presented, since as with other forms of gift authorship, QPQ falsifies the scholarly record. Finally, suggestions for future directions such as education for researchers are presented.
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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 | 0.016 | 0.148 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.014 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".