Bibliographic record
Abstract
The effect of pornography on the affect-arousal system has been studied extensively over the past four decades (Wright, 2013). One important aim has been to observe how exposure to pornographic materials impacts sexual beliefs and behaviors. An early report by the US Government (1971) acknowledged complex effects of pornography but in terms of risks and drawing causal conclusions viewed results to be inconclusive. Similar conclusions were reached by other western governments using population-wide correlational data (Fraser Committee, 1985; Williams, 1979). These studies with adult sex offender populations have yielded no consistent relationship between history of consuming pornography and engaging in sexual offenses (e.g., Bauserman, 1996; Ferguson & Hartley, 2009; Kerinel & Linders, 1996; Kingston, Fedoroff, Firestone, Curry & Bradford, 2008; Seto, Marc & Barbaree, 2001). Authors have also remarked on the inconsistencies between results from experimental studies with adults and those of a correlational nature with large populations (Ferguson & Hartley, 2009; Seto et al., 2001; Wright, 2013). It should be noted however that results have been viewed to be unequivocal when it comes to the impact of pornography on adolescent sexual attitudes and behaviors (Flood, 2009; Kunkel, Beily, Eyal, CopeFrarrar, Donnerstein & Fandrich, 2010; Strassburger, Jordan & Donnerstein, 2010). These authors have described how increased exposure to pornography has been shown to be related to more promiscuous attitudes toward sexual behavior, increased risk of STDs and unsafe sexual practices among teenagers. They have been quick to remind us also of the growing sexualization of youth culture through mainstream media such as television shows, films, magazines and cartoons (e.g., Flood, 2009). In the case of adults, experimental studies have shown that the relationship between repeated pornography exposure and aggressive sexual behavior among adults is mediated by a range of factors such as the violence content and whether or not the viewer is prone to engage in sexual violence (Allen, DAlessio & Brezgel, 1995; Malamuth, Addison & Koss, 2000). While some have argued that exposure to violent erotica can lead to greater engagement in sexual violence (Cramer & McFarlane, 1994; Kingston et al, 2008), others have observed no such relationship (Bauserman, 1996; Ferguson & Hartley, 2009; Kerinel & Linders, 1996). Put simply, most adults who view pornography regularly do not necessarily engage in violent acts and those who have been charged with violent and sexual offenses do not necessarily show a history of regular pornography use. Due to its inconclusive nature, researchers have advised caution before making inferences about individual behavior based on population-wide trends and vice-versa (Kingston, et al., 2008; Seto et al., 2001). This article aims to: (i) review theoretical models used to explain the relationship between pornography exposure and sexually deviant attitudes and behaviors; and (ii) present an application of a new model that can explain past findings and some anomalies in the literature. In doing so this paper will use the term 'pornography' in a broad manner involving media that contain significant levels of sexually explicit images and films. It should be noted, however, that fine distinctions have been made by researchers between the concepts of pornography and erotica (Malamuth, Addison & Koss, 2000; Welland & Muise, 2010). For example, erotica has often been observed to depict sexually intimate content that may not necessarily be directed at sexual gratification. These materials have also been described to be sexually evocative as opposed to sexually demeaning. Some have made distinctions between pornography that is violent and coercive in contrast to that which is softcore. Some in the field have acknowledged that these distinctions are largely subjective and many have pointed out how their impact on attitudes and behavior are dependent upon how viewers interpret images and scenarios presented in nude photo layouts and films based on their religious and political tastes, and how these concepts are operationalized by researchers (e. …
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".