The specificities of the Information System French-speaking scholar community in terms of journal prestige and publications.
Bibliographic record
Abstract
To respond to the identity crisis of the Information Systems (IS) disciple and agreeing with Hirsheim and Klein (2003), we believe that a "reflective analysis" can contribute to a favorable evolution of the discipline. Within the French-speaking community, such reflective analysis is needed to evaluate the journals in the IS field and their rankings in order to understand the production of the French-speaking researchers. The publishing process (how and where?) are fundamental components of the identity of the French-speaking community, as it reflects the community’s value systems, paradigms, cultural practices, systems of valuation, organizational structure and aspirations.This article analyzes the results of a scientometric study conducted on the Information Systems journals, targeting the French-speaking academic community. Unsurprisingly, Management Information Systems Quarterly (MISQ), which is considered the most prestigious journal in the IS world community, is also the most prestigious journal in the French-speaking community. In addition, this study allows us to rank the most prestigious journals from the point of view of French-speaking community. It shows a strong polarization of Frenchresearchers, unlike their colleagues in Quebec, toward publishing largely in journals whose the main editor-in-chief is or was European, English indeed.
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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 | 0.009 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.014 | 0.010 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".