Bibliographic record
Abstract
‘These are detestable murderers and scumbags, I'll tell you that right up front. They detest our freedoms, they detest our society, they detest our liberties.’ Canadian General Rick Heller, 16 July 2005 ‘The Taliban made some terrible mistakes, and I do not condone them. But I am also certain that we need a better understanding of how and why they made those mistakes before we condemn them. Many worse things have happened to Afghans than the Taliban government of 1996–2001 […] In the end the Taliban are only people, and surely deserve to be treated as such. I know they are capable of learning from their mistakes and of changing their minds.’ James Fergusson Other than the various mainsprings of external interest in Afghanistan and the trans- Indus regions in general, and the Pashtun cultures in particular, geopolitical developments during the 1980s and then specifically after September 11 understandably came to focus on the Taliban. Along with its reductionist portents, such a discourse reveals some shared themes such as political Islam, Taliban militancy and the security imperatives of the regional and global actors, which collectively converge in imparting or reiterating specific images about Muslim and especially the Pashtun communities. The juxtaposing of Islam with violence and Islamist movements as terrorist outfits cannot be seen in isolation, as they have become brand names and identikit for most Muslims. Irreverent of their ideological, denominational, class and national pluralities, such simplified views, more like those of the erstwhile communists and Jews, have unleashed severe ramifications. Appreciation of Muslim mundane dilemmas like those of any other human society is often absent in them, or it may reflect sheer indifference if not bland hostility. Certainly, there are numerous areas in which Muslim groups and states could perform better, yet their political and economic issues, especially those linked with some external factors need to be analysed objectively within their generic contexts. After all, the evolution of various forms of political Islam such as Hamas, Hezbollah, Islamic jihad, the Muslim Brotherhood, the Moro Liberation Army, the Jammu and Kashmir Liberation Front, the Hizbul Mujahideen, the Taliban and such other formulations overwhelmingly sought sustenance in political and economic grievances in which disempowerment, a grave sense of injustice, sustained oppression and dislocations had continued.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.016 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".