Bibliographic record
Abstract
The information age of the 21st century has transformed the economic, social, and political landscape in a profound and indelible manner. It also has changed the role and functions of government and redefined the scope and substance of good governance. Never before in human history has the pace of structural change been more pervasive, rapid, and global in its context. The information age has precipitated profound structural changes in the economic landscape and has given birth to the new economy. The new global economy is composed of a trilogy of interactive forces that include globalization, trade liberalization, and the information technology and communications revolution. Globalization has melted national borders, free trade has enhanced economic integration, and the information and communications revolution has made geography and time irrelevant (Passaris, 2001). Immigration has taken on a new perspective in the context of globalization. There is no denying that the spread of Internet-based technologies throughout society has become the dominant economic reality of the 21st century. E-economy—the use of information and communication technologies for product and process innovation across all sectors of the economy—has emerged as the primary engine of productivity and growth for the global economy. In large part due to advances in information and communications technologies, the role of international borders in this globalized economy has been transformed from the traditional geographical frontiers to virtual economic communities. Innovations in transportation and information and communications technology also has impacted immigration flows and made the world, in the phrase coined by Marshall McLuhan (1988), truly a “global village”. Borders have become less relevant for digital content communications and transactions. Cyberspace has no natural demarcations or border patrols. Indeed, knowledge-based products, such as software, games, and music, cross borders without impediment and with relative ease (Passaris, 2003). The advent of the information age has had a profound impact on the nature and scope of e-government and has given birth to the digital government of the 21st century. In particular, the interface between government and immigration management has been redesigned and restructured in terms of access to immigration information and application forms, the processing of immigration applicants for admission, enforcement of security measures and the prevention of terrorist infiltration, and the time line for adjudicating immigration applications, to name just a few of the significant changes to the contemporary process by which the governments of immigrant-receiving countries enforce their immigration policies.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 0.003 |
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".