From Modernization to Globalization: Challenges and Opportunities
Bibliographic record
Abstract
During the past decade, notions of globalization have displaced familiar discourses of modernization. On the political right, globalization is seen to signal the demise of socialist economies, and proponents of market liberalization proclaim new opportunities to further global wealth and prosperity. On the left, critics point to the ways in which the current economic restructuring is accompanied by an increasing gap between the ’haves’ and ’have nots’. However disparate these two positions seem, both neglect the gendered impact of globalization. The purpose of this article is to review feminist critiques ofglobalization. Central to this review is recognition of the diversity of women’s (and men’s) situations, both within and across cultures. This recognition reminds us that ’gender’cannot simply be added to existing paradigms ofglobalization. What is needed are innovative ways of thinking that will help us understand how local contexts are increasingly orchestrated by extra-local forces. The articles included in this Special Issue provide examples of such methodologies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.047 |
| Scholarly communication | 0.012 | 0.021 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.009 | 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".