The Linkages Between Productivity and Social Progress: An Introduction and Overview
Bibliographic record
Abstract
Productivity research is Canada has traditionally focused on narrow economic issues. In our view, it has given inadequate attention to the broader ramifications of productivity, both in terms of shedding light on the importance of productivity for the advancement of various aspects of social progress and in terms of understanding the feedback mechanisms running from social conditions and factors to productivity growth. The objective of the second issue of the Review of Economic Performance and Social Progress is to attempt to fill, at least in part, the lacuna in the literature in Canada on this two-way relationship between productivity and various aspects of social progress. The 15 papers in this volume (including the introduction) address the general issue of the linkages between productivity and various aspects of social progress. The papers are organized into five sections. The three papers in the first section discuss productivity concepts and trends in Canada and OECD countries. The two papers in the second section examine the impact productivity has on government balances and natural resources and environmental sustainability. In the third section, four papers explore the relationships between population, education, health and social divergence and productivity. In the fourth section, three papers address the theme of whether productivity should be a social priority, including discussion of the attitudes of Canadians to productivity. In the fifth and final section two papers examine the relationship between social policy, inequality and productivity. The purpose of this introduction is twofold. First, it provides a detailed overview of the main findings of all chapters in the volume. Second, it provides a synthesis of what the editors see as the main themes that emerge from the different chapters, including a discussion of the implications for public policy.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".