Bibliographic record
Abstract
Tahrir’s Youth: Leaders of a Leaderless Revolution offers vivid, intimate portraits of the youths who led the massive uprising that brought down the Mubarak regime in Egypt in 2011. The activism of these youths profoundly transformed contemporary Egyptian society, resulting in a series of political changes, many of which did not necessarily reflect the original intentions of the youths themselves. A decade after the historical events, the efforts, thoughts, and sacrifices of these young activists are still far from being sufficiently recognized by the popular narratives of recent Egyptian history. Instead, these popular accounts depict a “leaderless” revolution and highlight the role of Western social media in political activism. In Tahrir’s Youth, the author, Rusha Latif, powerfully challenges this narrative by offering a convincing story of how youths from a wide range of class and religious backgrounds engaged with each other and with the Egyptian people to mobilize and organize political activism. Latif situates her portraits of the revolutionary becoming of these young people in the historical context of the modernizing Egypt, that is, the socioeconomic order that was formed over the six decades from Nassar’s reign to Mubarak’s presidency. Rather than “leaderless,” “faceless,” and dependent on Western technology, the revolutionary story that Latif told has not only protagonists but also protagonists with biographic pre-revolutionary traces and post-revolutionary evolution. The author is not oblivious of the unique role that the Internet played in contemporary political activism. Arguing against an overly deterministic technological optimism, Tahrir’s Youth strikes a delicate balance between the social effects of information technology and the impact of these young actors’ political agency. The Internet, social media, and their associated networks are treated as important enabling conditions that shaped the trajectories of the historical course of these events but not as determining factors that exclusively account for the rise and fall of this political activism. Using Latif’s own words, “[the course of the events was]…neither thoroughly planned, nor completely spontaneous. Rather, it unfolded as part of a dialectical process in which purposeful actors and a historically determined contextual reality shaped one another through a series of rapidly evolving political actions and events that continuously transformed political actors and reconfigured their actions and subjectivities.” (Latif 2022, p. 153).
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".