24-liter Daypack Comparison

I recently decided to upgrade from my Deuter Speedlite 20 as the backpack I took for day-long outings with my family. The Speedlite has served me well for four years now, and remains my go to back for any number of other purposes, but for longer hikes, especially on warmer days, it clings to my back, collecting heat and sweat. (Thankfully, it dries quickly.) Its one-inch wide hip belt is not terribly comfortable, and its size means I can’t quite pack everything I would like, especially if I’d like to make it possible for a traveling companion to carry nothing. I already have a Deuter Futura 32, and so I know that it is more than I wanted, so I set my sights on something in the mid-twenties, 24 or 26 liters.

As fellow backpackers know, there are at least two categories of bags, if not really three, that occupy the 20 to 30 liter capacity range: the light packs, the standoff packs, and the technical packs. In the light category are Osprey’s Talon series, Deuter’s Speedlite series, and Gregory’s Miwok series. All fine packs, and reasonably comfortable with their various corrugated foam and mesh back panels, but not as comfortable as their slightly heavier cousins in Osprey’s Stratos series and Deuter’s Futura series. (Gregory’s offerings in the 20 liter range are Salvos, and then they shift to the Zulu line.) There are other backpack makers, I know, but I already owned both Osprey and Deuter packs and they have been super reliable for me: I use an Osprey Momentum 22 to commute to work and an Osprey Porter 46 for travel. I was familiar with Gregory, having looked at a Miwok pack before settling on the Osprey Momentum.

Deuter, Gregory, and Osprey also appear to be the only ones focused on making day packs with light metal frames and mesh backs that are comfortable on days you sweat. And so my comparison shopping came down to the Gregory Salvo 24, the Osprey Stratos 24, and the Deuter Futura 24. All good bags, but a couple of them are handicapped by recent design choices. In the case of the Deuter, the hip belt pockets have recently been dropped, and the hip belts themselves somewhat shrunken. In the case of the Osprey, they have gotten ride of the roomy outer stuff pocket in favor of some weird vertical zippered pocket that everyone agrees is useless when the pack is full.

That left the Gregory Salvo 24. It offered everything I wanted: 24 liter capacity, a large central compartment with panel access, a padded hip belt, with pockets, and a stuff pocket on the front. But I was not comfortable making a decision without some comparison, and so I added the Deuter Futura 26 into the mix: it’s a slightly taller bag, and one of the issues here is my torso. As a six foot plus tall man with 34″ legs, I have a longer torso, and finding a pack that gets the straps far enough up my back to reach my shoulders comfortably is unreasonably difficult. The Deuter Futura 26 is built like bigger packs: it has a spindrift collar, a brain, and while it doesn’t have a front stash pocket, it does offer easy access to the main compartment via a zippered panel.

I wore both packs around the house with a gallon bucket of paint stashed inside: its bulky and heavy (and it was handy). Both packs seemed fine. I then took them out to a nearby park, again with the can of paint handy, and walked around with them. While the Deuter was a bit taller, it also felt like it was fighting me a little bit, and the Gregory just seemed more comfortable, which may in part be a function of the pack staying a little closer to my back. (This feature may become a bug, since obviously there will be less air between my back and the pack, but I cannot know that within the window I have to make a decision.)

So, in breaking with a long tradition of only owning Osprey and Deuter packs, with a couple of Timbuk2 shoulder bags, it looks like a Gregory is joining the family. I’ll post a photo from an upcoming hike as soon as I have one.

New Book Thursday

Julia Flanders and Fotis Jannidis. 2018. The Shape of Data in Digital Humanities: Modeling Texts and Text-based Resources. Routledge.

Data and its technologies now play a large and growing role in humanities research and teaching. This book addresses the needs of humanities scholars who seek deeper expertise in the area of data modeling and representation. The authors, all experts in digital humanities, offer a clear explanation of key technical principles, a grounded discussion of case studies, and an exploration of important theoretical concerns. The book opens with an orientation, giving the reader a history of data modeling in the humanities and a grounding in the technical concepts necessary to understand and engage with the second part of the book. The second part of the book is a wide-ranging exploration of topics central for a deeper understanding of data modeling in digital humanities. Chapters cover data modeling standards and the role they play in shaping digital humanities practice, traditional forms of modeling in the humanities and how they have been transformed by digital approaches, ontologies which seek to anchor meaning in digital humanities resources, and how data models inhabit the other analytical tools used in digital humanities research. It concludes with a glossary chapter that explains specific terms and concepts for data modeling in the digital humanities context. This book is a unique and invaluable resource for teaching and practising data modeling in a digital humanities context.

For those of you thinking “Oh, no, Routledge. I can’t afford it. You are correct.” This was not the promise the internet made to knowledge distribution.

AFS 2018

For those who have asked, below are links to the paper I gave at this year’s meeting of the American Folklore Society along with the slides and the handout (which was a version of the slides, so you don’t need both). As I catch up with everything on which I have fallen behind, I will post my notes about the conference itself in some fashion.

Here are: the paper, the slides, and the handout for “It’s about Time: How Folk Narratives Manage Time in Discourse.”

Abstract: Concluding his consideration of “Time in Folk-Narrative,” Bill Nicolaisen noted that the nature of human experience is centrally of time and that what marked genres of folk narrative, perhaps as much, or more, than anything else, was their management of time: “What must be stressed, however, is that in contrast to the concepts and realization of an extended present and of narrated time in the folktale, the dramatic comparisons made in the legend are designed to demonstrate the incompatibility of the two time frames, which exist as parallel systems” (318). Much of Nicolaisen’s efforts are focused on a careful compilation of how time is signaled, and thus managed, within the discourse of ten fairy tales drawn randomly from Thompson’s One Hundred Favorite Folktales. This paper revisits and extends Nicolaisen’s work, taking as its central task the careful attention to words used. Where Nicolaisen focused principally on the folktale, with occasional references to legend, this paper, part of a larger examination of legends in the current moment, uses a number of legends taken, first, from oral discourse, and then a number of legends found online. It follows this examination with a look at, what the paper itself argues, is the adjacent genre of the personal anecdote, sometimes also known as the personal experience narrative, in order to determine how a close examination of the management of time, in discourse, might reveal where the two genres converge or diverge, in hopes of finding a better way to model both and reliable discursive cues. Some of the methodologies deployed are computational in nature, beginning with forms of markup first explored by computer scientists Pustejovsky et alum and followed up by recent attempts to automate temporal signals in texts by David Elson. The current work seeks to re-imagine the pioneering work of Bill Nicolaisen, and before him Benjamin Colby, in light of recent developments in computational modeling of narrative with an especial focus on what that means for the study of genre.

Nicolaisen, William. 1978. Time in Folk-Narrative. In Folklore Studies in the Twentieth Centuries, 314-319. Ed. Venetia Newall. Rowman and Littlefield. (Available as a PDF.)

Nicolaisen on “The Structure of Narrated Time in the Folktale”

As I work on my paper for this year’s annual meeting of the American folklore society, I find myself treasuring one of a collection of offprints once sent to me by Bill Nicolaisen. I am pretty sure that others will find his work compelling and that the conference proceedings in which it appeared, Journées d’Études en Littérature Orale: Analyse des contes, problèmes de méthodes, is probably pretty hard to find. Here’s a PDF version. (The OCR is okay, not great: I’m working on am improved scan.)

Text Analytics APIs 2018

Text Analytics APIs 2018: A Consumer Guide is $895 for a single user license. At 299 pages, that’s about $3 per page. The blurb notes that:

Robert Dale is an internationally-recognized expert in Natural Language Processing, with three decades of experience in academia and industry. With a PhD from the University of Edinburgh, he’s worked for Microsoft and Nuance, and he’s driven the development of SaaS-based NLP software for a startup. He has taught at the University of Edinburgh in the UK and at Macquarie University in Sydney, and presented tutorials and summer school courses around the world. He has over 150 peer-reviewed publications, including a comprehensive Handbook of Natural Language Processing, and the de facto textbook Building Natural Language Generation Systems.

LitRPGs

Audible emailed me about “LitRPGs”, a genre about which I have heard little. I imagined something like Choose-Your-Own-Adventure or Cortazar’s “Hopscotch” but it seems to cover a pretty wide range of texts.

Ternary Color Scheme

I was interested in the data for the age of European populations, but I found myself more taken with the color scheme used in the visualization:

Ternary Representation of European Populations by Age (Web Size)

A full-sized version of the image is available on request — it’s really big. But the map is part of an article in The Lancet.

Transcription in 2018

The range of transcription options has opened up considerably since I last considered the possibility of turning over some, but not all, transcription to software. It appears to be largely done in the cloud, with offerings from the following:

  • Transcribe appears to be simply an on-line version of the mechanical transcription machines I used to use: load the audio and then type. The “automagic” version allows you to listen to the audio through a headset and then dictate it to the site, which will then transcribe. That’s interesting.
  • f4transkript is another on-line service where you load your audio and then you do the typing.

If you’re interested in these traditional forms of transcription, wherein you do the typing, then may I also suggest you check out the transcription options in Scrivener. It’s not a service, so you just buy the software and use it. And a license is very inexpensive.

For those interested in letting an AI of some kind transcribe the audio for you — ah, the future, then there appears to be Descript. It appears to be the case that you upload your files either online, or you simply load them into an app installed on your local machine: it’s not quite clear if you pursue the latter course if the transcription takes place entirely on your machine or if the AI that does the heavy lifting lives in the cloud. The demos appear to work in real time, but the site suggests that perhaps you can load an audio of whatever length as a digital file and in less time than it takes to play it, you can have a transcript back.

I’m going to see how much you can do with a free account and report back. This could be very, very useful. (And cool!)