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.
Bibliographic record
Abstract
Modeling of virtual organization (VO) can be a useful method of making sense of a plethora of organizations that are proclaimed to be “virtual,” “virtualized,” or to exhibit “virtualness.” Since the advent of these notions (Byrne, 1993; Davidow & Malone, 1992; Mowshowitz, 1994), an enormous proliferation of VOs has followed in theory and practice across academic disciplines and industries. Being “virtual” had almost become a fashion embraced by corporations and other businesses, groups of organizations engaged in cooperation/collaboration or trading, libraries, schools, government organizations, non-government organizations, churches, museums, and so on. The implication of these developments is that it has become difficult to reach an agreement on what VO is beyond the customary agreement at a lexical level. Lexically, the virtual character refers to a potentiality and effect that divert from the actual appearance of a virtual thing (Webster, 1988). Thus, a VO is an effect of interaction of what in fact are different organizations or constituents of organizations (groups and individuals). Introduced by inventors of VO, this axiom has remained undisputed to date.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it