"Racially Charged": Negotiating Black Politics on the Superhero TV Adaptation, Black Lightning
Bibliographic record
Abstract
This project takes Black Lightning as a case study of the representations of Black superheroes in comic book television adaptations.By focusing on the three main superheroes Jefferson Pierce/Black Lightning; Anissa Pierce/Thunder/Black Bird; and Jennifer Pierce/Lightning, this project examines the ways in which the show relies on the superhero semantics and mediates Black Christianity to negotiate Black political thought and respond to contemporary racial politics in the US.More precisely, it focuses on Jefferson's representation as an actor of Black respectability politics; Anissa's positioning as a radical activist and superhero often in conflict with the politics of respectability; and finally, Jennifer's political reawakening at a moment when the "postracial" myth is prevalent in the US.daughters, representing the Generation X, Generation Y/Millennial, and Generation Z cohorts, respectively.These three characters reflect, inflect, and deflect Black politics differently. Black Lightning: A Case StudyBlack Lightning, originally created by Tony Isabella and Trevor von Eeden, was the first Black superhero to debut his own title, which ran for thirteen issues beginning in 1977.The comic book launched as a "self-titled" series when Isabella, who is white, was hired at DC Comics to create a new Black superhero (Nama, 2011, p. 25).He had previously created Luke Cage at Marvel and took on the challenge of introducing "[t]he electricity wielding Black Lightning" who "was actually Jefferson Pierce, an ex-Olympian turned inner-city schoolteacher with a passion for cleaning up the ghetto in which he lived and worked" (Brown, 2000, p. 24, emphasis added).Nearly fifty years after Black Lightning #1 was first published, Salim Akil and Mara Brock Akil recreated Black Lightning's world for television, but he now shares the spotlight with his daughters, Anissa and Jennifer.Jefferson's electricity-based powers were triggered at a young age after getting exposed to a substance used by a secret government agency to create metahumans.Peter Gambi, his father's friend and a former agent of this secret agency, rescued Jefferson and trained him to become a superhero.Situated in the fictional American city of Freeland in 2017, we are told that Jefferson had retired as a superhero nine years ago, because his superheroism was interfering with his role as a father.His commitment to his community, however, remained intact, so he accepted a role as a high school principal to aid Black youth and prevent them from choosing the wrong path of joining the ever-growing 100 Gang.The show starts off with Jefferson Pierce's return as Black Lightning in 2017 to
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.017 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".