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These realizations are not ruled out by anything that is specified in a canonical description of the case. But then necessity is false. For related reasons, it is hard to see how mere reflection on the case — under some such description — could give us justification to believe necessity .

Someone might object as follows: ‘Why is it a problem for the target rationalist that the judgement she ascribes to us is false and unjustified? Surely it is still an open question at this stage of the inquiry whether any given intuitive judgement is true and/or justified? Careful analysis of its content may reveal that it fails on both scores.’

Let me reply on Williamson’s behalf: as I understand it, the problem is not simply that the candidate content is false and/or unjustified — the problem is that it is too obviously false and unjustified. Our intuitive judgements may indeed be in poor epistemic shape, but it would be highly surprising if it turned out to be this easy to reveal that they are. Indeed, it would be surprising enough if it were this easy to show that the Gettier judgement alone was in poor shape — the usual presumption being that, if any intuitive judgement is in good standing, it is the Gettier judgement. But matters are worse, since parallel arguments are available for many other intuitive judgements. 22

Next, the proposal under consideration is a psychological hypothesis about the content of our actual judgement, and as such it makes certain predictions that are not borne out. We simply do not behave as we would behave if the proposal were true. In particular, we do not take the possibility of the above realizations of the case to falsify our original intuitive judgement. And on the face of it, this reaction is appropriate — it is not just a result of stubbornness or a reluctance to admit mistakes. Rather, the reason why we do not retract or revise our original judgement is that the envisaged realizations do not agree with our (semantic) intuitions about what the case designer meant . (By ‘case designer’ I just mean whoever put together the case description. The case designer and the thought experimenter may of course coincide.) These realizations of the case are deviant , and they are easily recognizable as such. That is, the corresponding interpretations of the case description are clearly unintended  — the description was not meant to be read in some such way — and we rightly ignore these interpretations when running the thought experiment. And when it is pointed out to us that it can be filled out in some such way, we do not retract our original intuitive judgement or start qualifying it (e.g. by adding ‘what I should have said is that Jones does not know —  provided that there is no other route to knowledge available to him’). 23 This suggests that necessity fails to capture the intended generality of that judgement.

Note how even though all of the chapters in this example are added backwards, they come out in the proper order:

Collections with a comparator will not automatically re-sort if you later change model attributes, so you may wish to call sort after changing model attributes that would affect the order.

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will sort itself whenever a model is added. To disable sorting when adding a model, pass {sort: false} to add . Calling sort triggers a "sort" event on the collection.

pluck collection.pluck(attribute) Pluck an attribute from each model in the collection. Equivalent to calling map and returning a single attribute from the iterator.

where collection.where(attributes) Return an array of all the models in a collection that match the passed attributes . Useful for simple cases of filter .

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url collection.url or collection.url() Set the url property (or function) on a collection to reference its location on the server. Models within the collection will use url to construct URLs of their own.

parse collection.parse(response, options) parse is called by Backbone whenever a collection's models are returned by the server, in fetch . The function is passed the raw response object, and should return the array of model attributes to be added to the collection. The default implementation is a no-op, simply passing through the JSON response. Override this if you need to work with a preexisting API, or better namespace your responses.

clone collection.clone() Returns a new instance of the collection with an identical list of models.

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. The server handler for fetch requests should return a JSON array of models.

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