Don’t be Afraid of the Boogeyman: Media Narratives Surrounding the Death of Derek Boogaard
Bibliographic record
Abstract
Within research on mental health in professional sports, mental illness has been recognized as a threat to athletes’ personal and professional lives. In 1996, the National Hockey League Players Association (NHLPA) and National Hockey League (NHL) emphasized the importance of improving mental wellness among athletes by implementing the Substance Abuse and Behavioral Health program (SABH) into their Collective Bargaining Agreement (CBA). However, since establishing this program, players suffering from mental illness have not always received the appropriate care and treatment necessary for recovery. In 2011, the NHL witnessed the deaths of three of its players – Derek Boogaard, Rick Rypien and Wade Belak – all related to mental health disorders. While highlighting players suffering from mental illness is now within the media, stories are often published that individualize mental illness without capturing the destructive aspects of sports culture, which often play a great role in the genesis of poor mental health and addiction among athletes. The present study examined how North American print and digital news stories narrated the death of Derek Boogaard, who died of an accidental overdose of oxycodone and alcohol at 28 years old. Boogaard's case was analyzed to examine if/how mental illness was narrated within news media from May 13th, 2011 - August 13th, 2011. Key findings included three central narratives: “sensationalizing physicality, aggression and violence,” “overlooking pain and injuries,” and “idolizing Boogaard’s off-ice persona.” Together, these three narratives demonstrate that media narratives often align with the values of hockey culture. This allowed researchers to better understand how "problematic" athletes are individualized within the news media, as opposed to addressing the culture of risk and denial deeply rooted in the sport of hockey.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".