Bibliographic record
Abstract
Although many scholars (Cooke, Tribal Modern: Branding New Nations in the Arab Gulf . Berkeley: University of California Press, 2014; Foley, The Arab Gulf States: Beyond Oil and Islam . Boulder, CO: Lynne Rienner Publishers, 2010; Gray, Qatar: Politics and the Challenges of Development . Boulder, CO: Lynne Rienner Publishers, 2013) have documented the impact of oil and gas wealth in transforming Qatar from a “traditional society” into a modern one, the speed at which Qatar has developed over the past 15–20 years is still striking. Almost overnight the small state’s foreign population has increased dramatically. The resulting demographic imbalance and the rapid urbanization and development have had a tremendous impact on Qatari society. The focus of this chapter is to look at how this rapid transformation has affected the family in Qatar in general and the role of women in particular. We examine the centrality of women in state polices that attempt to address the challenges that face the family. We begin by arguing that the state’s policy toward the family, which was developed during the process of state formation, has unintentionally undermined the extended family. We examine how many, if not most, of functions of the traditional tribal extended family have been replaced by state agencies. However, the transformation of society has occurred at such a fast pace that the relevant agencies and institutions have had difficulty coping with or anticipating the new responsibilities with such a shift. This situation, we suggest, led the government to retroactively enact policies that target issues or “problems” that have emerged in society as a result of major changes taking place in Qatar. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.013 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.015 | 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".