Investigating journal peer review as scientific object of study: unabridged version – Part I
Bibliographic record
Abstract
The main goal of this paper is to construct journal peer review as a scientific object of study based on historical research into its shaping. This paper is a first in a two-part series. Journal peer review performed in the natural sciences has been an object of study since at least 1830. Researchers mostly implicitly frame it as a rational system with expectations of rational decision-making. This in spite of research debunking rationality where journal peer review can yield low inter-rater reliability, be purportedly biased and conservative, and cannot readily detect fraud or misconduct. Furthermore, journal peer review is consistently presented as a process started in 1665 at the first journals and as holding a gatekeeper function for quality science. In contrast, socio-historical research portrays journal peer review as emulating previous social processes regulating what is to be considered as scientific knowledge (or not) (cf., inquisition, censorship) and early learned societies as engaged in peer review with a legal obligation under censorship. However, to date few researchers have sought to investigate journal peer review beyond a pre-constructed process or self-evident object of study based on common experience. Here I construct journal peer review as a scientific object of study with key analytical dimensions based on its structural properties. I use the theoretical concept of social form to capture how individuals relate around a particular content. For the social form of ‘boundary judgement’ (i.e., journal peer review), content refers to decisions from the judgement of scientific written texts held to account to an overarching knowledge system. Given its roots in censorship with its function of bounding science, I frame journal peer review as following precursor boundary judgement forms of inquisition and censorship. Constructing journal peer review as a scientific object of study contributes to improving it based on scientific understanding.
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
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | high |
| gpt | MetaresearchScience and technology studiesScholarly communication Domain: Evaluation · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Qualitative | high |
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 | 0.044 | 0.048 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".