Conclusion

Abstract

The breakdown of the idyll as the vehicle for a morally concerned and more or less realistic exploration of life’s major problems—especially problems in relations between the sexes and between different classes—is signalled most dramatically by the early novels of Hardy. Despite the charm and authenticity of many of their ‘Dutch pictures’ of rustic life Under the Greenwood Tree and Far from the Madding Crowd belie their idyllic titles, the former partly, the latter almost totally. Although, to Hardy’s chagrin, their original reviewers made much of their indebtedness to the early pastoral novels of George Eliot—particularly Adam Bede—and although their close-knit rural communities and customary ways are ostensibly even remoter from the ugliness and contention of the modern industrial world than are Hayslope and Raveloe, Under the Greenwood Tree and Far from the Madding Crowd implicitly hold out less hope of a complete, or even an imaginatively and morally satisfying, resolution of the issues they raise than do any of Eliot’s early novels. In Far from the Madding Crowd (1874), as in Adam Bede, irreconcilable individuals precipitate tragedy, or at any rate ‘catastrophe’;1 and even in Under the Greenwood Tree, where tragedy never threatens, minor doubts and uncertainties about the fitness of the young lovers for their idyllic roles, and for each other, take on magnified, even disproportionate significance. Even the least troubled love affairs in Hardy’s novels—including that of Fancy Day and Dick Dewy in Under the Greenwood Tree—exhibit a characteristic, and disturbing, imbalance between the man’s sexual ardour and emotional commitment and the woman’s; and the measure of the imbalance is often the extent to which, on one side or the other, ardour is dampened by class-consciousness.KeywordsRealistic ExplorationTrue StoryMarriage NightGenuine FriendshipDisproportionate SignificanceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.