Reviewing Globalization: Three Competing Stories, Two Emerging Themes, and How Law Schools Can and Must Participate
Bibliographic record
Abstract
Globalization means many things to many people. For some, it leads to a welcomed opening of parochial dogmas and ideas. It brings great wealth and opportunity, through trade, open markets and the free-flow of capital, to large numbers of populations and sectors across the globe. Once foreign and inaccessible goods and services are now readily available at our corner stores and through our computer screens. Globalization links people, literally and virtually, through increased mobility and technology. All of these changes are heralded by many as the birth of a new, post-1989 world era of globalization. At the same time, globalization is seen by others as the creator of massive disparities in wealth, power and opportunity among local and global populations. Allowing Western corporations increasingly to access the raw materials and labour of developing societies facilitates the exploitation of people, economies and environments. International trade regimes - the WTO, NAFTA, FTAA, APEC, etc. - allow largely unelected international trade officials and dispute resolution panels to influence and often determine domestic choices and policy decisions about labour rights, environmental initiatives, export policies and budgetary initiatives. The result of this upward migration of power is a growing discontent and disenfranchisement of non-governmental grassroots organizations and domestic political constituents.
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 | 0.042 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.027 | 0.064 |
| Scholarly communication | 0.042 | 0.040 |
| Open science | 0.005 | 0.018 |
| Research integrity | 0.018 | 0.023 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".