Book Review: Teaching against Islamophobia, Teaching Critical Thinking: Practical Wisdom, Cultural-Historical Perspectives on Teacher Education and Development: Learning Teaching
Bibliographic record
Abstract
This book represents a committed and comprehensive attempt to remind those in society who define themselves as educators that embracing issues of social justice and equity implies taking sides in the Islamophobia debate.The editors rightfully view Islamophobia through the lens of racism.In the United Kingdom, this has led to the use of the term 'anti-Muslim racism' instead of Islamophobia.Though the editors claim in their foreword that the book is aimed at teachers, the contributions make it clear that it is intended for a much broader audience and that it has been especially written to make all of us (and non-Muslims primarily) reflect on our attitudes and misconceptions and to rethink many of our assumptions.The 20 chapters in this book cover a wide range of topics, and it moves from more theoretical and socio-political discourse to a discussion of more practical issues.In chapter 1, Kincheloe & Steinberg set the theoretical tone for the rest of the book.Their comment that 'learning from difference means that teachers are aware of the histories and struggles of colonized groups and oppressed peoples' (p.4) signifies how the authors reject the very common approach in multicultural and intercultural education that avoids discussing historical injustices and controversial issues so as not to upset people.Their statement, which they build on in their further analysis, echoes Paul Gorski's challenge to 'decolonize' intercultural education when attempting to deal with education about diversity (Gorski, 2008).References to empathetic understanding, solidarity and valuing of differences help position their pedagogical approach.Very useful in this chapter is the deconstruction of the propagandistic arguments being used by, for instance, the Fordham Foundation to promote the West and especially the (Christian) United States as enlightened and majority Muslim nations as inherently inferior and a threat.Part 2 of the book is entitled 'Reading Islamophobia' and contains four chapters that look at public, media and political discourse.Shirley Steinberg returns to the topic of media discourse.In this fifth chapter, she first examines 17 films where there is a significant presence of Arabs and/or Muslims.Her analysis shows that without exception, the overwhelming majority of Muslims/Arabs depicted in films -for most films the two are interchangeable categories -are viewed as barbaric, dangerous and uncivilized.Steinberg also deconstructs popular television programmes such as cable television's Sleeper Cell and 24 (she mentions that 24 is Dick Cheney's favourite programme).On the whole, Muslims are perceived as potential threats and especially as the 'enemy within'.Given their evil demeanour and the threat to the United States, they do not deserve the same rights as others in society.The author closes with the interesting observation that '[t]his Hollywood diet is not innocent: It is constructed on obsession, stereotype, fear, and, more importantly, on what sells' (p.96).Chapters 9, 10 and 13 examine a topic often forgotten in the discourse about Islam and Muslims in the United States -the relationship of the African American community to Islam.Preacher Moss, who refers to himself as an 'undercover Muslim', takes a somewhat tongue-in-cheek look at African American perspectives on Muslim identities.The more serious essence of his treatise is that 'African American Muslims are marginalized as African Americans and ignored as African American Muslims' (p.163).Samaa Abdurraqib provides, in her chapter, highly insightful
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.030 | 0.013 |
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".