Individuals with Multi-Institutional Profiles: Construct Development and Operationalization
Bibliographic record
Abstract
This conceptual paper has three overarching objectives. The first is to propose a new construct for cross-cultural research, which we refer to as an individual’s multi-institutional profile (MIP). Defining this construct as personal characteristics indicative of exposure to and at least partial internalization of transcultural values and norms that are likely to shape an individual’s cognitions, decisions and behaviors, we suggest that individuals with an MIP represent a hitherto overlooked set of agents who contribute to intra-cultural differences and processes of cultural change. Our second objective is to offer suggestions for operationalizing the MIP construct. We do this by delineating illustrative demographic measures and then providing examples of how these separate indicators can be combined to form an aggregate measure reflecting the strength of an individual’s MIP. Our third objective is to discuss how the separate and/or aggregate measures of the MIP construct can be examined empirically within a wide range of academic fields —including international business, entrepreneurship/family business, and organizational behavior.
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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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".