Bibliographic record
Abstract
Many corporations fail to find the Holy Grail of globalization because they have not paid “enough” ongoing attention to the process. Without greater attentional effectiveness in their efforts to globalize, firms waste precious executive resources or decide to standardize their operations to limit the complexity of their international strategies. Neither of these reactions is desirable. While companies can deploy a range of helpful tools in increasing overall levels of global attention, these tools are costly and not every company is in a position to achieve and sustain high levels of global attention effectively. In this article, the authors discuss three dimensions of management attention: aversion/attraction, captive/voluntary, and front‐of‐mind/back‐of‐mind. Each of these dimensions provides an array of tools to focus management attention. By maximizing each of these dimensions, attention effectiveness is increased. In an international business world with abundant information, managers need to focus on their most scarce resource – management attention.
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 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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.010 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.079 | 0.033 |
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".