MétaCan
Menu
Back to cohort
Record W2337888258 · doi:10.1177/0047117815585888

The struggle over the identity of IR: What is at stake in the disciplinary debate within and beyond academia?

2015· article· en· W2337888258 on OpenAlexaff
Félix Grenier, Helen Louise Turton, Philippe Beaulieu-Brossard

Bibliographic record

VenueInternational Relations · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Relations and Foreign Policy
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsDisciplineSociologySubject (documents)EpistemologyIdentity (music)InstitutionField (mathematics)PoliticsInternational relationsState (computer science)Social sciencePolitical scienceLawAestheticsLibrary science

Abstract

fetched live from OpenAlex

Since the inception of International Relations (IR) within university departments, its disciplinary status has been the subject of constant debate. Yet, the current literature on ‘the state of the discipline’ silences this debate either through IR’s assumed disciplinarity or conflation of debates about theory with the existence of IR. This Forum moves beyond this literature by explicitly engaging whether IR is a discipline or not and by enquiring how this status matters. Contributors rely on the sociology and philosophy of social science to call into question or affirm the disciplinarity of IR to argue whether IR is as a subfield of Political Science, a full-blown and autonomous discipline, or a hybrid field of interdisciplinary studies. Furthermore, contributors reveal the implications of the different disciplinary statuses regarding the academic institution, interdisciplinary possibilities and modes of organizing IR. Overall, these contributions aim to engage rather than close the disciplinary debate, creating further space for reflection.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.094
metaresearch head score (Gemma)0.076
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score0.499

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0940.076
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.008
Science and technology studies0.0310.131
Scholarly communication0.0850.053
Open science0.0040.021
Research integrity0.0180.028
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.046
GPT teacher head0.378
Teacher spread0.333 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueInternational RelationsSame topicInternational Relations and Foreign PolicyFrench-language works237,207