MétaCan
Menu
Back to cohort
Record W2093084344 · doi:10.1016/j.jssr.2014.10.001

Beyond the “Babel Problem”: Defining Simulations for the Social Studies

2014· article· en· W2093084344 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Social Studies Research · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicInnovative Teaching Methodologies in Social Sciences
Canadian institutionsSt. Mary's University
Fundersnot available
KeywordsConflationField (mathematics)EpistemologyDynamismVerisimilitudeCLARITYConsistency (knowledge bases)PhenomenonSocial simulationSociologyMediationComputer scienceManagement scienceSocial science

Abstract

fetched live from OpenAlex

Simulation research has become a growing area of interest in the social studies in recent years. Problematically, the term simulation is used without consistency among practitioners and researchers. The conceptual confusion regarding what simulations are (or are not) muddies the field and makes it difficult for scholars to make sense of this phenomenon or to talk about simulations across findings. In order to bring clarity to the field, this paper is framed around two conceptual and analytic constructs: conceptual analysis and the theory of language games. In this paper, I will provide a rationale for why the social studies field requires a specific definition for simulations. Next, simulations will be defined using four specific criteria: verisimilitude, dynamism, active human agents, and pedagogical mediation. Finally, simulations will be differentiated from three related phenomena with which they are often conflated: games, role-plays, and models.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.096
metaresearch head score (Gemma)0.043
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesMetaresearch, Science and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.771
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0960.043
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0400.013
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.628
GPT teacher head0.639
Teacher spread0.011 · 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