Bibliographic record
Abstract
This volume arises out of a large research endeavour, known as the Trends Project, organized and financed by the Government of Canada's Policy Research Secretariat and the Social Sciences and Humanities Research Council of Canada (SSHRCC), in Ottawa.After extensive consultation, these two agencies identified eight different "trends" for sustained research and analysis by multidisciplinary teams of social scientists.Team leaders were named for each of the trends -in the case of globalization, Janice Gross Stein and David R. Cameron -and were asked to join a committee to choose the members of the various teams by means of a competitive process.Requests for proposals were posted on the Social Sciences and Humanities Research Council Web site, and the team members were selected from the pool of applicants who responded.From the start, the team leaders responsible for the globalization trend intended to approach this complex phenomenon as a social and cultural process.A great deal has been said and written about the economics of globalization, but less about its social and cultural dimensions.The request for proposals placed a premium on imaginative ideas, and we were delighted by the variety and creativity of the projects we were able to select.We understood from the outset that a systematic and comprehensive examination of the social and cultural dimensions of globalization would be beyond the reach of this enterprise.However, we believe that the essays in this volume address some of the most important but less studied dimensions of globalization as a social and cultural process, as well as its consequences for Canada.The essays should be regarded as explorations of a highly complex phenomenon central to modern human existence and to Canada's fate in the coming decades.We would like to take this opportunity to thank the people who made this project possible.Laura Chapman, the head of the Policy Research Secretariat in Ottawa, offered her strong support to the Trends Project in general and to our globalization project in particular.We are grateful to
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.350 | 0.159 |
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".